Journal articles: 'ROI tracking'

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Chandran, Deepak R. "Return on Investment (ROI) for Asset (Tools) Tracking." Journal of Advanced Research in Embedded System 05, no. 03 (July 6, 2018): 1–6. http://dx.doi.org/10.24321/2395.3802.201801.

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Lv, Ying. "Typhoon Cloud Tracking by Kalman Filter." Applied Mechanics and Materials 58-60 (June 2011): 2487–92. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2487.

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Typhoon cloud has its changeability, so it is difficult to track and predict compared with the rigid targets. Region of interest (ROI) and reference region were selected by using interactive methods. Bezier curve is used to smooth the gray level histogram of ROI and obtain Bezier histogram. The gray level value which is corresponding to the valley of the Bezier histogram is used to segment the ROI in order to get the tracking target. And target parameters could be predicted by using Kalman filter, then getting the moving track of the target. Experimental results show that the proposed algorithm has nice real-time ability and adaptability.

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Zhao, Yue, Adeline Bernard, Christian Cachard, and Hervé Liebgott. "Biopsy Needle Localization and Tracking Using ROI-RK Method." Abstract and Applied Analysis 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/973147.

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ROI-RK method is a biopsy needle localization and tracking method. Previous research work has proved that it has a robust performance on different series of simulated 3D US volumes. Unfortunately, in real situations, because of the strong speckle noise of the ultrasound image and the different echogenic properties of the tissues, the real 3D US volumes have more complex background than the simulated images used previously. In this paper, to adapt the ROI-RK method in real 3D US volumes, a line-filter enhancement calculation only in the ROI is added to increase the contrast between the needle and background tissue, decreasing the phenomenon of expansion of the biopsy needle due to reverberation of ultrasound in the needle. To make the ROI-RK method more stable, a self-correction system is also implemented. Real data have been acquired on anex vivoheart of lamb. The result of the ROI-RK method shows that it is capable to localize and track the biopsy needle in real situations, and it satisfies the demand of real-time application.

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ZHANG, JING, LI ZHUO, and YINGDI ZHAO. "REGION OF INTEREST DETECTION BASED ON VISUAL PERCEPTION MODEL." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 02 (March 2012): 1255005. http://dx.doi.org/10.1142/s0218001412550051.

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According to human vision theory, the image is conveyed from human visual system to brain when people have a look at. Different from previous work, the study reported in this paper attempts to simulate a more real and complex method for region of interest (ROI) detection and quantitatively analyze the correlation between users' visual perception and ROI. In this paper, a visual perception model-based ROI detection is proposed, which can be realized with an ordinary web camera. Visual perception model employs a combination of visual attention model and gaze tracking data to objectively detect ROIs. The work includes pre-ROI estimation using visual attention model, gaze data collection and ROI detection. Pre-ROIs are segmented by the visual attention model. Since eye feature extraction is critical to the accuracy and performance of gaze tracking, adaptive eye template and neural network are employed to predict gaze points. By computing the density of the gaze points, ROIs are ranked. Experimental results show that the accuracy of our ROI detection method can be raised as high as 97% and it is also demonstrated that our model can efficiently adapt to users' interests and match the objective ROI.

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Tanaka, Midori, Matteo Paolo Lanaro, Takahiko Horiuchi, and Alessandro Rizzi. "Random Spray Retinex Extensions Considering Region of Interest and EyeMovements." Electronic Imaging 2020, no. 15 (January 26, 2020): 60403–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.15.color-349.

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The Random spray Retinex (RSR) algorithm was developed by taking into consideration the mathematical description of Milano-Retinex. The RSR substituted random paths with random sprays. Mimicking some characteristics of the human visual system (HVS), this article proposes two variants of RSR adding a mechanism of region of interest (ROI). In the first proposed model, a cone distribution based on anatomical data is considered as ROI. In the second model, the visual resolution depending on the visual field based on the knowledge of visual information processing is considered as ROI. We have measured actual eye movements using an eye-tracking system. By using the eye-tracking data, we have simulated the HVS using test images. Results show an interesting qualitative computation of the appearance of the processed area around real gaze points.

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Tanaka, Midori, Matteo Paolo Lanaro, Takahiko Horiuchi, and Alessandro Rizzi. "Random Spray Retinex Extensions Considering Region of Interest and Eye Movements." Journal of Imaging Science and Technology 63, no. 6 (November 1, 2019): 60403–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.6.060403.

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Abstract The Random spray Retinex (RSR) algorithm was developed by taking into consideration the mathematical description of Milano-Retinex. The RSR substituted random paths with random sprays. Mimicking some characteristics of the human visual system (HVS), this article proposes two variants of RSR adding a mechanism of region of interest (ROI). In the first proposed model, a cone distribution based on anatomical data is considered as ROI. In the second model, the visual resolution depending on the visual field based on the knowledge of visual information processing is considered as ROI. We have measured actual eye movements using an eye-tracking system. By using the eye-tracking data, we have simulated the HVS using test images. Results show an interesting qualitative computation of the appearance of the processed area around real gaze points.

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Wynn, Leslie. "Tracking Tool Helps Deliver ROI from Early-Stage Design Insights." Design Management Review 29, no. 2 (June 2018): 32–43. http://dx.doi.org/10.1111/drev.12126.

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Rehman, Bacha, Wee Hong Ong, Abby Chee Hong Tan, and Trung Dung Ngo. "Face detection and tracking using hybrid margin-based ROI techniques." Visual Computer 36, no. 3 (March 27, 2019): 633–47. http://dx.doi.org/10.1007/s00371-019-01649-y.

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Yen, Shwu-Huey, Chun-Hui Wang, and Jui-Chen Chien. "Accurate and robust ROI localization in a camshift tracking application." Multimedia Tools and Applications 74, no. 23 (July 16, 2014): 10291–312. http://dx.doi.org/10.1007/s11042-014-2167-z.

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Yousefi, Bardia, Hossein Memarzadeh Sharifipour, Mana Eskandari, Clemente Ibarra-Castanedo, Denis Laurendeau, Raymond Watts, Matthieu Klein, and Xavier P. V. Maldague. "Incremental Low Rank Noise Reduction for Robust Infrared Tracking of Body Temperature during Medical Imaging." Electronics 8, no. 11 (November 7, 2019): 1301. http://dx.doi.org/10.3390/electronics8111301.

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Thermal imagery for monitoring of body temperature provides a powerful tool to decrease health risks (e.g., burning) for patients during medical imaging (e.g., magnetic resonance imaging). The presented approach discusses an experiment to simulate radiology conditions with infrared imaging along with an automatic thermal monitoring/tracking system. The thermal tracking system uses an incremental low-rank noise reduction applying incremental singular value decomposition (SVD) and applies color based clustering for initialization of the region of interest (ROI) boundary. Then a particle filter tracks the ROI(s) from the entire thermal stream (video sequence). The thermal database contains 15 subjects in two positions (i.e., sitting, and lying) in front of thermal camera. This dataset is created to verify the robustness of our method with respect to motion-artifacts and in presence of additive noise (2–20%—salt and pepper noise). The proposed approach was tested for the infrared images in the dataset and was able to successfully measure and track the ROI continuously (100% detecting and tracking the temperature of participants), and provided considerable robustness against noise (unchanged accuracy even in 20% additive noise), which shows promising performance.

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Chung, Yao-Liang, Hung-Yuan Chung, and Wei-Feng Tsai. "Hand gesture recognition via image processing techniques and deep CNN." Journal of Intelligent & Fuzzy Systems 39, no. 3 (October 7, 2020): 4405–18. http://dx.doi.org/10.3233/jifs-200385.

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In the present study, we sought to enable instant tracking of the hand region as a region of interest (ROI) within the image range of a webcam, while also identifying specific hand gestures to facilitate the control of home appliances in smart homes or issuing of commands to human-computer interaction fields. To accomplish this objective, we first applied skin color detection and noise processing to remove unnecessary background information from the captured image, before applying background subtraction for detection of the ROI. Then, to prevent background objects or noise from influencing the ROI, we utilized the kernelized correlation filters (KCF) algorithm to implement tracking of the detected ROI. Next, the size of the ROI image was resized to 100×120 and input into a deep convolutional neural network (CNN) to enable the identification of various hand gestures. In the present study, two deep CNN architectures modified from the AlexNet CNN and VGGNet CNN, respectively, were developed by substantially reducing the number of network parameters used and appropriately adjusting internal network configuration settings. Then, the tracking and recognition process described above was continuously repeated to achieve immediate effect, with the execution of the system continuing until the hand is removed from the camera range. The results indicated excellent performance by both of the proposed deep CNN architectures. In particular, the modified version of the VGGNet CNN achieved better performance with a recognition rate of 99.90% for the utilized training data set and a recognition rate of 95.61% for the utilized test data set, which indicate the good feasibility of the system for practical applications.

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Yates, Kirsty. "Managing, tracking and evaluating coaching part 2: where could you be?" Industrial and Commercial Training 47, no. 2 (March 2, 2015): 95–98. http://dx.doi.org/10.1108/ict-08-2014-0058.

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Purpose – The purpose of this paper is to offer a number of recommendations that will enable you to get your hands around the coaching that is taking place inside your organisation so that you can manage it better and, moreover, calculate the commercial and cultural returns your organisation is achieving from the coaching in light of research presented in the author's previous article. Design/methodology/approach – This research is based on a case study. Findings – Although not an easy task, it is possible to evaluate the impact of coaching and, in turn, calculate the return on investment (ROI). Key to doing this is that each relationship should be set up correctly; the coach should be fully qualified, experienced and in supervision and information regarding the volume, status and expenditure of each coaching contract must be kept up to date and, along with evaluation data for each contract, used to measure the impact of coaching to the organisation and to calculate the ROI. Originality/value – The case study included shows how coaching has been transformed in E.ON UK since outsourcing all aspects of its coaching, resulting in a clear and robust process generating valuable data on the impact of individual contracts and the programme as a whole, as well as an ROI.

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Pearson, Stephen J., Tim Ritchings, and Ahmad S. A. Mohamed. "The Use of Normalized Cross-Correlation Analysis for Automatic Tendon Excursion Measurement in Dynamic Ultrasound Imaging." Journal of Applied Biomechanics 29, no. 2 (April 2013): 165–73. http://dx.doi.org/10.1123/jab.29.2.165.

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The work describes an automated method of tracking dynamic ultrasound images using a normalized cross-correlation algorithm, applied to the patellar and gastrocnemius tendon. Displacement was examined during active and passive tendon excursions using B-mode ultrasonography. In the passive test where two regions of interest (2-ROI) were tracked, the automated tracking algorithm showed insignificant deviations from relative zero displacement for the knee (0.01 ± 0.04 mm) and ankle (–0.02 ± 0.04 mm) (P> .05). Similarly, when tracking 1-ROI the passive tests showed no significant differences (P> .05) between automatic and manual methods, 7.50 ± 0.60 vs 7.66 ± 0.63 mm for the patellar and 11.28 ± 1.36 vs 11.17 ± 1.35 mm for the gastrocnemius tests. The active tests gave no significant differences (P> .05) between automatic and manual methods with differences of 0.29 ± 0.04 mm for the patellar and 0.26 ± 0.01 mm for the gastrocnemius. This study showed that automatic tracking of in vivo displacement of tendon during dynamic excursion under load is possible and valid when compared with the standardized method. This approach will save time during analysis and enable discrete areas of the tendon to be examined.

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Boumediene, Mohammed, Jean-Philippe Lauffenburger, Jeremie Daniel, Christophe Cudel, and Abdelaziz Ouamri. "Multi-ROI Association and Tracking With Belief Functions: Application to Traffic Sign Recognition." IEEE Transactions on Intelligent Transportation Systems 15, no. 6 (December 2014): 2470–79. http://dx.doi.org/10.1109/tits.2014.2320536.

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Fernández‐Berni, J., R. Carmona‐Galán, R. Río, and Á. Rodríguez‐Vázquez. "High dynamic range adaptation for ROI tracking based on reconfigurable concurrent dual‐sensing." Electronics Letters 50, no. 24 (November 2014): 1832–34. http://dx.doi.org/10.1049/el.2014.3136.

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YUN, BYOUNG-JU, JOONG-HOON CHO, and JAE-WOO JEONG. "REAL-TIME OBJECT TRACKING IN MOVING CAMERA." International Journal of Information Acquisition 03, no. 01 (March 2006): 61–67. http://dx.doi.org/10.1142/s0219878906000836.

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Moving object tracking plays an important role in applications of object based video conference, video surveillance and so on. The computational complexity is very important in real-time object tracking. We assumed that the background scene is obtained before an object appears in the image and a camera moves after the object is detected. The proposed method can segment an object by using the difference image if there is no camera motion. After camera motion, it can track the object by using the backward BMA (block matching algorithm) with the HFM (human figure model). For real-time tracking, we used the ROI (region of interest) which is the tightest rectangle of the object. The simulation results show that the proposed method efficiently recognizes and tracks the moving camera as well as the fixed camera.

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Khamis, Hanan, Sara Shimoni, Andreas Hagendorff, Nahum Smirin, Zvi Friedman, and Dan Adam. "Feasibility of reproducible vendor independent estimation of cardiac function based on first generation speckle tracking echocardiography." Journal of Biomedical Engineering and Informatics 2, no. 2 (December 27, 2015): 57. http://dx.doi.org/10.5430/jbei.v2n2p57.

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Background: The clinical approval of speckle tracking echocardiography (STE) as an accepted measure of myocardial strain and of LV function is hindered by the discordance of the results among the vendors. Since echocardiography images are noisy, the measured displacements are smoothed or regularized, an operation affecting the strain results. We introduce an “Error-dependent weighted speckle tracking” (EWST) algorithm that allows sensitivity analysis to the different operations affecting noise and accuracy. The aim here was to study whether by modifying the properties of the post block-matching weighted smoothing in the EWST algorithm it was possible to assess the expected inter-vendor strain differences. Methods and results: 48 echocardiographic clips generated by a software-based phantom were used as “gold standard” for validation of the EWST algorithm. Also, a cohort of 435 normal subjects and a cohort of 47 patients, scanned/re- scanned at 2 frame-rates (~70; ~35), were studied using the EWST. The results were compared to those produced by a commercial product of a leading manufacturer (STELV). Peak global longitudinal strains [PRLS, (%)] and peak regional longitudinal strains [PRLS, (%)] were calculated and compared. Sensitivity to the region (ROI) determination was tested by shifting the apical endocardial boundary. The differences between the measured PGLS and the ground truth produced by the software-based phantom (average ± standard deviation) were 0.4% ± 0.6% and 1.0% ± 0.7% for the EWST and STELV, respectively. Normal values were calculated for 435 subjects: -18.82% ± 2.45%, -20.2% ± 5.6%, -19.62% ± 3.62%, 18.77% ± 4.31% by the EWST, and -21.24% ± 2.91%, -26.5% ± 5.0%, -21.1% ± 3.7%, -18.0% ± 3.9%, by the STELV, respectively, for the PGLS, the peak longitudinal apical, mid-ventricle and basal regions, respectively. A low bias, but significant, was found between PGLS, when calculated for the cohort of 47 patients scanned/re-scanned at 2 frame-rates: -0.80% ± 2.61% and -1.66% ± 2.66% for the EWST and STELV, respectively. When the apex location (and thus the ROI) was shifted, the bias (mm) (average ± standard deviation) relative to the default position was: 0.82 ± 1.04; 0.61 ± 0.72; -1.06 ± 0.75; and -1.87 ± 0.72, for displacement of 5 cm, 2.5 cm, -2.5 cm, and -5 cm, respectively, for the STELV. The EWST proved similarly sensitive to the shifting of the apex location. Conclusions: STE is sensitive to the characteristics and amount of smoothing, as well as to the ROI positioning. Modification of the smoothing can produce different stain results, and different distribution of the regional strains. Thus it is preferable to use automatic determination of the ROI and methods that employ minimal smoothing or regularization.

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Jiang, Shenlu, Wei Yao, Zhonghua Hong, Ling Li, Cheng Su, and Tae-Yong Kuc. "A Classification-Lock Tracking Strategy Allowing a Person-Following Robot to Operate in a Complicated Indoor Environment †." Sensors 18, no. 11 (November 12, 2018): 3903. http://dx.doi.org/10.3390/s18113903.

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Person-following technology is an important robot service. The major trend of person-following is to utilize computer vision technology to localize the target person, due to the wide view and rich information that is obtained from the real world through a camera. However, most existing approaches employ the detecting-by-tracking strategy, which suffers from low speed, accompanied with more complicated detecting models and unstable region of interest (ROI) outputs in unexpressed situations. In this paper, we propose a novel classification-lock strategy to localize the target person, which incorporates the visual tracking technology with object detection technology, to adapt the localization model to different environments online, and to keep a high frame-per-second (FPS) on the mobile platform. This person-following approach consists of three key parts. In the first step, a pairwise cluster tracker is employed to localize the person. A positive and negative classifier is then utilized to verify the tracker’s result and to update the tracking model. In addition, a detector pre-trained by a CPU-optimized convolutional neural network is used to further improve the result of tracking. In the experiment, our approach is compared with other state-of-art approaches by a Vojir tracking dataset, with three sequences in the items of human to prove the quality of person localization. Moreover, the common challenges during the following task are evaluated by several image sequences in a static scene, and a dynamic scene is used to evaluate the improvement from the classification-lock strategy. Finally, our approach is deployed on a mobile robot to test its performance on the function of the person-following. Compared with other state-of-art methods, our approach achieves the highest score (0.91 recall rate). In the static and dynamic scene, the output of the ROI based on the classification-lock strategy is significantly better than that without it. Our approach also succeeds in a long-term following task in an indoor multi-floor scenario.

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WATANABE, Daisuke, Kenji ONO, and Xizoyang MAO. "Identificatio of ROI in 3D Flow Field Using Eye Tracking Data and Autormatic Streamline Placement." Journal of the Visualization Society of Japan 27, Supplement2 (2007): 119–20. http://dx.doi.org/10.3154/jvs.27.supplement2_119.

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Wang, Zhao, and Jun Ohya. "An Algorithm for Tracking Guitarists’ Fingertips Based on CNN-Segmentation and ROI Associated Particle Filter." Journal of Imaging Science and Technology 63, no. 2 (March 1, 2019): 20506–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.2.020506.

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Jeong, Hyo-Won, Joo-Young Ha, Hag-Yong Han, Hoon-Gee Yang, and Bong-Soon Kang. "Face Region Tracking Improvement and Hardware Implementation for AF(Auto Focusing) Using Face to ROI." Journal of the Korean Institute of Information and Communication Engineering 14, no. 1 (January 30, 2010): 89–96. http://dx.doi.org/10.6109/jkiice.2010.14.1.089.

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Abdul-Kreem, Luma Issa, and Hussam K. Abdul-Ameer. "Object tracking using motion flow projection for pan-tilt configuration." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (October 1, 2020): 4687. http://dx.doi.org/10.11591/ijece.v10i5.pp4687-4694.

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We propose a new object tracking model for two degrees of freedom mechanism. Our model uses a reverse projection from a camera plane to a world plane. Here, the model takes advantage of optic flow technique by re-projecting the flow vectors from the image space into world space. A pan-tilt (PT) mounting system is used to verify the performance of our model and maintain the tracked object within a region of interest (ROI). This system contains two servo motors to enable a webcam rotating along PT axes. The PT rotation angles are estimated based on a rigid transformation of the the optic flow vectors in which an idealized translation matrix followed by two rotational matrices around PT axes are used. Our model was tested and evaluated using different objects with different motions. The results reveal that our model can keep the target object within a certain region in the camera view.

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Dhaliwal, Pawandeep Kaur. "An Implementation of Non-Contact Respiratory Monitoring System with Advanced Nasal-Mandible Tracking Algorithm with Roi." International Journal for Research in Applied Science and Engineering Technology V, no. VIII (August 29, 2017): 409–15. http://dx.doi.org/10.22214/ijraset.2017.8057.

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Zhao, Yue, Christian Cachard, and Hervé Liebgott. "Automatic Needle Detection and Tracking in 3D Ultrasound Using an ROI-Based RANSAC and Kalman Method." Ultrasonic Imaging 35, no. 4 (September 30, 2013): 283–306. http://dx.doi.org/10.1177/0161734613502004.

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Xu, Ziyi, Quchao Wang, Duo Li, Menghan Hu, Nan Yao, and Guangtao Zhai. "Estimating Departure Time Using Thermal Camera and Heat Traces Tracking Technique." Sensors 20, no. 3 (January 31, 2020): 782. http://dx.doi.org/10.3390/s20030782.

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Advancement in science and technology is playing an increasingly important role in solving difficult cases at present. Thermal cameras can help the police crack difficult cases by capturing the heat trace on the ground left by perpetrators, which cannot be spotted by the naked eye. Therefore, the purpose of this study is to establish a thermalfoot model using thermal imaging system to estimate the departure time. To this end, in the current work, we use a thermal camera to acquire the thermal sequence left on the floor, and convert it into the heat signal via image processing algorithm. We establish the model of thermalfoot print as we observe that the residual temperature would exponentially decrease with the departure time according to Newton’s Law of Cooling. The correlation coefficients of 107 thermalfoot models derived from the corresponding 107 heat signals are basically above 0.99. In a validation experiment, a residual analysis is conducted and the residuals between estimated departure time points and ground-truth times are almost within a certain range from −150 s to +150 s. The reverse accuracy of the thermalfoot model for estimating departure time at one-third, one-half, two-thirds, three-fourths, four-fifths, and five-sixths capture time points are 71.96%, 50.47%, 42.06%, 31.78%, 21.70%, and 11.21%, respectively. The results of comparison experiments with two subjective evaluation methods (subjective 1: we directly estimate the departure time according to obtained local curves; subjective 2: we utilize auxiliary means such as a ruler to estimate the departure time based on obtained local curves) further demonstrate the effectiveness of thermalfoot model for detecting the departure time inversely. Experimental results also demonstrated that the thermalfoot model has good performance on the departure time reversal within a short time window someone leaves, whereas it is probably only approximately 15% to accurately determine the departure time via thermalfoot model within a long time window someone leaves. The influence of outliers, ROI (Region of Interest) selection, ROI size, different capture time points and environment temperature on the performance of thermalfoot model on departure time reversal can be explored in the future work. Overall, the thermalfoot model can help the police solve crimes to some extent, which in turn brings more guarantees for people’s health, social security, and stability.

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LIU Hui, 刘辉, 何勇 HE Yong, 何博侠 HE Bo-xia, 刘志 LIU Zhi, and 顾士晨 GU Shi-chen. "Infrared Target Tracking Algorithm Based on Multiple Feature Fusion and Region of Interest Prediction." ACTA PHOTONICA SINICA 48, no. 7 (2019): 710004. http://dx.doi.org/10.3788/gzxb20194807.0710004.

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Bao, Min, Guyo Chala Urgessa, Mengdao Xing, Liang Han, and Rui Chen. "Toward More Robust and Real-Time Unmanned Aerial Vehicle Detection and Tracking via Cross-Scale Feature Aggregation Based on the Center Keypoint." Remote Sensing 13, no. 8 (April 7, 2021): 1416. http://dx.doi.org/10.3390/rs13081416.

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Unmanned aerial vehicles (UAVs) play an essential role in various applications, such as transportation and intelligent environmental sensing. However, due to camera motion and complex environments, it can be difficult to recognize the UAV from its surroundings thus, traditional methods often miss detection of UAVs and generate false alarms. To address these issues, we propose a novel method for detecting and tracking UAVs. First, a cross-scale feature aggregation CenterNet (CFACN) is constructed to recognize the UAVs. CFACN is a free anchor-based center point estimation method that can effectively decrease the false alarm rate, the misdetection of small targets, and computational complexity. Secondly, the region of interest-scale-crop-resize (RSCR) method is utilized to merge CFACN and region-of-interest (ROI) CFACN (ROI-CFACN) further, in order to improve the accuracy at a lower computational cost. Finally, the Kalman filter is adopted to track the UAV. The effectiveness of our method is validated using a collected UAV dataset. The experimental results demonstrate that our methods can achieve higher accuracy with lower computational cost, being superior to BiFPN, CenterNet, YoLo, and their variants on the same dataset.

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Maier, Mathias, Ali Nasseri, Carsten Framme, Sabrina Bohnacker, Matthias Becker, Dominik Heinrich, Hansjürgen Agostini, Nikolaus Feucht, Chris Lohmann, and Lars Hattenbach. "Die intraoperative optische Kohärenztomografie in der Netzhaut-Glaskörper-Chirurgie. Aktuelle Erfahrungen und Ausblick auf künftige Entwicklungsschritte." Klinische Monatsblätter für Augenheilkunde 235, no. 09 (June 9, 2017): 1028–34. http://dx.doi.org/10.1055/s-0043-106304.

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Zusammenfassung Hintergrund Die hochauflösende optische Kohärenztomografie (OCT) ermöglicht eine kontrastreiche Bildgebung von Mikrostrukturen, die mit konventioneller Bildgebung nicht so detailliert darstellbar waren. Wir berichten über unsere Erfahrungen beim Einsatz der intraoperativen OCT (iOCT) in der vitreoretinalen Chirurgie. Methoden 110 Patienten mit vitreoretinalen Erkrankungen (Makulaforamen, epiretinale Membranen, vitreomakulärem Traktionssyndrom, Ablatio und Glaskörperblutung) wurden unter Visualisierung mit dem im Mikroskop integrierten iOCT-Gerät operiert. Ergebnisse Das iOCT liefert durch die Integration von Mikroskop und SD-OCT eine sofortige Visualisierung der „Region of Interest“ (ROI). Der Operateur erhält neben dem Mikroskopbild die intraoperative Darstellung aller Netzhautschichten, des Glaskörpers sowie der Instrument-Gewebe-Interaktion in Echtzeit und kann diese intraoperativ sofort verfügbare Information für die chirurgische Strategie nutzen. Schlussfolgerung Bisher ist das iOCT nur als Standmikroskop erhältlich, es besitzt keine Messfunktion, keine Tracking-Funktion, und die Metallinstrumente verdecken den Scan. Künftig könnten transparente Instrumente, Tracking-Funktionen, ein Autofokus sowie eine noch bessere Auflösung eine optimierte, lückenlose, hochauflösende intraoperative OCT-Diagnostik in Echtzeit erlauben.

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Jaafar, Haryati, Salwani Ibrahim, and Dzati Athiar Ramli. "A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier." Computational Intelligence and Neuroscience 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/360217.

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Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-basedknearest centroid neighbor (IFkNCN), was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%.

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Goga, Cristina, Zeynep Firat, Klara Brinzaniuc, and Is Florian. "Meyer’s Loop Anatomy Demonstrated Using Diffusion Tensor MR Imaging and Fiber Tractography at 3T." Acta Medica Marisiensis 60, no. 5 (October 1, 2014): 215–22. http://dx.doi.org/10.2478/amma-2014-0045.

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Abstract Objective: The ultimate anatomy of the Meyer’s loop continues to elude us. Diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) may be able to demonstrate, in vivo, the anatomy of the complex network of white matter fibers surrounding the Meyer’s loop and the optic radiations. This study aims at exploring the anatomy of the Meyer’s loop by using DTI and fiber tractography. Methods: Ten healthy subjects underwent magnetic resonance imaging (MRI) with DTI at 3 T. Using a region-of-interest (ROI) based diffusion tensor imaging and fiber tracking software (Release 2.6, Achieva, Philips), sequential ROI were placed to reconstruct visual fibers and neighboring projection fibers involved in the formation of Meyer’s loop. The 3-dimensional (3D) reconstructed fibers were visualized by superimposition on 3-planar MRI brain images to enhance their precise anatomical localization and relationship with other anatomical structures. Results: Several projection fiber including the optic radiation, occipitopontine/parietopontine fibers and posterior thalamic peduncle participated in the formation of Meyer’s loop. Two patterns of angulation of the Meyer’s loop were found. Conclusions: DTI with DTT provides a complimentary, in vivo, method to study the details of the anatomy of the Meyer’s loop.

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G. Abo Samra and O. AbdulKader, G. Abo Samra and O. AbdulKader. "A New Technique Based on Intensity Distribution Graphs for the Extraction of Traffic Flow Rate and Vehicle Speed." journal of king abdulaziz university computing and information technology sciences 1, no. 2 (January 10, 2012): 1–24. http://dx.doi.org/10.4197/comp.1-2.1.

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This paper introduces a new visual system which allows analysis of traffic behavior on freeways and highways, using a video camera mounted on a relatively high place (such as a bridge). A new technique based on spatial and temporal intensity distribution is introduced to determine the road traffic parameters: average speed (AVSP) and average flow rate (AVFL). After performing many steps including automatic detection of the Region Of Interest (ROI) and camera orientation, background subtraction and Inverse Perspective Mapping (IPM), an Intensity Distribution Graph (IDG) is built for the current frame. The (IDG) is then transformed into a single Grayscale Image Line (GIL). A certain number (N) of GILs representing N frames are concatenated to build a Vehicle Tracking Diagram image (VTD) which gives a whole view of the traffic flow in the ROI during a specific period T. Using the VTD we can visualize the vehicles trajectories, speeds and estimate AVFL. By applying edge detection and Hough Line transform on the VTD, AVSP is estimated. The system has been implemented using MATLAB as an offline application. The results were encouraging, reaching 97% accuracy for the AVSP and AVFL. Further code optimization is needed for online monitoring.

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Guo, Xiaoying, Liang Li, Akira Asano, and Chie Muraki Asano. "Influences of Global and Local Features on Eye-Movement Patterns in Visual-Similarity Perception of Synthesized Texture Images." Applied Sciences 10, no. 16 (August 11, 2020): 5552. http://dx.doi.org/10.3390/app10165552.

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Global and local features are essential for visual-similarity texture perception. Therefore, understanding how people allocate their visual attention when viewing textures with global or local similarity is important. In this work, we investigate the influences of global and local features of a texture on eye-movement patterns and analyze the relationship between eye-movement patterns and visual-similarity selection. First, we synthesized textures by separately controlling global and local textural features through the primitive, grain, and point configuration (PGPC) texture model, a mathematical morphology-based texture model. Second, we conducted an experiment to acquire eye-movement data where participants identified the texture that was highly similar to the standard texture. Experiment data were obtained through an eye-tracker from 60 participants. The collected eye-tracking data were analyzed in terms of three metrics, including total fixation duration in each region of interest (ROI), fixation-point variance in each ROI, and fixation-transfer counts between different ROIs. Analysis results indicated the following. (1) The global and local features of a texture influenced eye-movement patterns. In particular, the texture image that was globally similar to the standard texture contained dispersed fixation points. By contrast, the texture image that was locally similar to the standard texture contained concentrated fixation points. The domination of global and local features influenced the viewers’ similarity choice. (2) The final visual-similarity selection was related to the fixation-transfer count between different ROIs, but not to the fixation time in each ROI. This research also extends the applicability of the mathematical morphology-based texture model to human visual perception.

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Mulimani, neshwari, and Aziz Makandar. "Sports Video Annotation and Multi- Target Tracking using Extended Gaussian Mixture model." International Journal of Recent Technology and Engineering 10, no. 1 (May 30, 2021): 1–6. http://dx.doi.org/10.35940/ijrte.a5589.0510121.

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Video offers solutions to many of the traditional problems with coach, trainer, commenter, umpires and other security issues of modern team games. This paper presents a novel framework to perform player identification and tracking technique for the sports (Kabaddi) with extending the implementation towards the event handling process which expands the game analysis of the third umpire assessment. In the proposed methodology, video preprocessing has done with Kalman Filtering (KF) technique. Extended Gaussian Mixture Model (EGMM) implemented to detect the object occlusions and player labeling. Morphological operations have given the more genuine results on player detection on the spatial domain by applying the silhouette spot model. Team localization and player tracking has done with Robust Color Table (RCT) model generation to classify each team members. Hough Grid Transformation (HGT) and Region of Interest (RoI) method has applied for background annotation process. Through which each court line tracing and labeling in the half of the court with respect to their state-of-art for foremost event handling process is performed. Extensive experiments have been conducted on real time video samples to meet out the all the challenging aspects. Proposed algorithm tested on both Self Developed Video (SDV) data and Real Time Video (RTV) with dynamic background for the greater tracking accuracy and performance measures in the different state of video samples.

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Kitai, Takaaki, and Takasi Haraguchi. "Optimal Scan Timing in 64-Row MDCT Angiography of the Lower Extremities: 2-Point ROI Detection Bolus-Tracking Method." Japanese Journal of Radiological Technology 67, no. 1 (2011): 51–56. http://dx.doi.org/10.6009/jjrt.67.51.

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Weiß Lucas, C., I. Tursunova, V. Neuschmelting, H. Lockau, C. Nettekoven, A. M. Oros-Peusquens, G. Stoffels, et al. "P115. The predictive value of FAT and MFL for deterministic, NTMS-based fibre tracking using a multiple-ROI approach." Clinical Neurophysiology 126, no. 8 (August 2015): e105-e106. http://dx.doi.org/10.1016/j.clinph.2015.04.157.

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Wu, Bin, Chunmei Wang, Wei Huang, Da Huang, and Hang Peng. "Recognition of Student Classroom Behaviors Based on Moving Target Detection." Traitement du Signal 38, no. 1 (February 28, 2021): 215–20. http://dx.doi.org/10.18280/ts.380123.

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Classroom teaching, as the basic form of teaching, provides students with an important channel to acquire information and skills. The academic performance of students can be evaluated and predicted objectively based on the data on their classroom behaviors. Considering the complexity of classroom environment, this paper firstly envisages a moving target detection algorithm for student behavior recognition in class. Based on region of interest (ROI) and face tracking, the authors proposed two algorithms to recognize the standing behavior of students in class. Moreover, a recognition algorithm was developed for hand raising in class based on skin color detection. Through experiments, the proposed algorithms were proved as effective in recognition of student classroom behaviors.

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Gordon, G. T., and B. P. McCann. "Basis for the development of sustainable optimisation indicators for activated sludge wastewater treatment plants in the Republic of Ireland." Water Science and Technology 71, no. 1 (November 24, 2014): 131–38. http://dx.doi.org/10.2166/wst.2014.482.

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This paper describes the basis of a stakeholder-based sustainable optimisation indicator (SOI) system to be developed for small-to-medium sized activated sludge (AS) wastewater treatment plants (WwTPs) in the Republic of Ireland (ROI). Key technical publications relating to best practice plant operation, performance audits and optimisation, and indicator and benchmarking systems for wastewater services are identified. Optimisation studies were developed at a number of Irish AS WwTPs and key findings are presented. A national AS WwTP manager/operator survey was carried out to verify the applied operational findings and identify the key operator stakeholder requirements for this proposed SOI system. It was found that most plants require more consistent operational data-based decision-making, monitoring and communication structures to facilitate optimised, sustainable and continuous performance improvement. The applied optimisation and stakeholder consultation phases form the basis of the proposed stakeholder-based SOI system. This system will allow for continuous monitoring and rating of plant performance, facilitate optimised operation and encourage the prioritisation of performance improvement through tracking key operational metrics. Plant optimisation has become a major focus due to the transfer of all ROI water services to a national water utility from individual local authorities and the implementation of the EU Water Framework Directive.

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Tsao, Shun-Hsien, Yu-Luen Chen, Jhe-Jyu Luh, Jin-Shin Lai, Te-Son Kuo, and Han-Shuan Wu. "PEDESTRIAN TRAFFIC LIGHT RECOGNITION FOR THE VISUALLY IMPAIRED." Biomedical Engineering: Applications, Basis and Communications 19, no. 05 (October 2007): 289–94. http://dx.doi.org/10.4015/s1016237207000380.

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In this research, we employ the technology of computer vision to recognize traffic light. We manipulate the color information of traffic light under HSI color space. And then, adding motor tracking technology, we can trap the traffic light which is subjected to a region of interest (ROI) to the center area of monitor. Meanwhile, we assign different frequency (peach) according to red light or green light to inform the people what state the light is. We develop the algorithm at PC with MATLAB. Then, we port the whole system to DSP platform TI TMS320 DM642 EVM. The result is that in the condition of non-complex environment, the system can distinguish the red light from green light, and also can output audio signal by means of speaker.

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Yang, Hui Bao. "Research on Lane Departure Warning System." Applied Mechanics and Materials 598 (July 2014): 731–35. http://dx.doi.org/10.4028/www.scientific.net/amm.598.731.

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Lane departure warning system includes lane identification and lane departure determination. Lane identification is crucial for lane departure warning system. In this paper, A linear mode which can only bring out small distance error and angle error is used to detect lane boundaries. A region of interest (ROI) appropriate is set to reduce nonessential cost of computation. According to the characteristics of lane position, we improve the Hough transform, reduce the detection and tracking transform angle and raise the speed of calculation. Parameter angle form Hough transform is used to lane departure determination, this method does not calibrate the camera and can get the lane departure rate. Experiments show that the system is well to detect and track the lane line and give alarm correctly.

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Yates, Kirsty. "Managing, tracking and evaluating coaching Part 1: where are you now?" Industrial and Commercial Training 47, no. 1 (February 2, 2015): 36–41. http://dx.doi.org/10.1108/ict-08-2014-0057.

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Purpose – The purpose of this paper is to understand the extent to which clients manage, track and evaluate coaching within their organisation, including awareness of the number of individuals being coached, awareness of their annual coaching spend, existence of a consistent and robust process for tracking all coaching, quality assurance processes in existence, and the evaluation of the impact of coaching. Design/methodology/approach – Semi-structured telephone interviews with HR, OD and L&D Directors and Managers in 69 large UK organisations collectively employing approximately 688,000 people. Findings – Whilst a handful of organisations are very satisfied with how coaching is managed, the vast majority feel there is room for improvement. The research highlights a number of issues: more than half the respondents do not know how many of their employees are currently working with an external coach and less than half are involved in a three-way meeting to sign off the coaching objectives at the beginning of the contract. In terms of evaluation and ROI, less than one in seven organisations have calculated their return on coaching investment, despite some organisations spending well in excess of £100k per year. Originality/value – Whilst the prevalence and benefits of coaching have been discussed at length over recent years, despite significant resources being invested in coaching there appeared to be very little research on how coaching is being resourced, managed and tracked in organisations. To that end, The Learning Curve (TLC) Ltd commissioned Adsum to investigate this research gap.

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Chang, Oscar, Patricia Constante, Andrés Gordon, and Marco Singaña. "A Novel Deep Neural Network that Uses Space-Time Features for Tracking and Recognizing a Moving Object." Journal of Artificial Intelligence and Soft Computing Research 7, no. 2 (April 1, 2017): 125–36. http://dx.doi.org/10.1515/jaiscr-2017-0009.

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Abstract This work proposes a deep neural net (DNN) that accomplishes the reliable visual recognition of a chosen object captured with a webcam and moving in a 3D space. Autoencoding and substitutional reality are used to train a shallow net until it achieves zero tracking error in a discrete ambient. This trained individual is set to work in a real world closed loop system where images coming from a webcam produce displacement information for a moving region of interest (ROI) inside the own image. This loop gives rise to an emergent tracking behavior which creates a self-maintain flow of compressed space-time data. Next, short term memory elements are set to play a key role by creating new representations in terms of a space-time matrix. The obtained representations are delivery as input to a second shallow network which acts as “recognizer”. A noise balanced learning method is used to fast train the recognizer with real-world images, giving rise to a simple and yet powerful robotic eye, with a slender neural processor that vigorously tracks and recognizes the chosen object. The system has been tested with real images in real time.

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Ma, Jishan, and Hongyan Liao. "Trend-Tracking Trading Strategy Based on Improved RSI: A Case Study of Chinese CSI 300 Stock Index Futures." International Journal of Economics and Finance 9, no. 4 (March 12, 2017): 130. http://dx.doi.org/10.5539/ijef.v9n4p130.

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In European and American developed countries, quantitative trading is gradually replacing artificial transactions to occupy an important position in the market, and their daily turnover in the market is particularly evident. China securities market and derivatives market started late, and have a relatively obvious difference from abroad, especially in Western countries, in the level of quantitative transactions in mature capital markets. With the improvement of China’s market trading varieties, China’s quantization will develop very rapidly. In this paper, according to the characteristics of China’s CSI 300 Index Futures, we improve trend-tracking trading model based on the improved RSI. Firstly, we apply the wavelet transform for denoising of the price series, then improve RSI, and use the improved RSI and the denoised price series to establish an exit strategy and approach strategy. The strategy is excellent in practical application. In 1 minute K-line data back-test of CSI 300 index futures from 2010 to 2012, the return on invest has reached up to 102 million Yuan, and the ROI risk ratio is 2.61.

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Jacquesson, Timothee, Fang-Chang Yeh, Sandip Panesar, Jessica Barrios, Arnaud Attyé, Carole Frindel, Francois Cotton, Paul Gardner, Emmanuel Jouanneau, and Juan C. Fernandez-Miranda. "Full tractography for detecting the position of cranial nerves in preoperative planning for skull base surgery: technical note." Journal of Neurosurgery 132, no. 5 (May 2020): 1642–52. http://dx.doi.org/10.3171/2019.1.jns182638.

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OBJECTIVEDiffusion imaging tractography has allowed the in vivo description of brain white matter. One of its applications is preoperative planning for brain tumor resection. Due to a limited spatial and angular resolution, it is difficult for fiber tracking to delineate fiber crossing areas and small-scale structures, in particular brainstem tracts and cranial nerves. New methods are being developed but these involve extensive multistep tractography pipelines including the patient-specific design of multiple regions of interest (ROIs). The authors propose a new practical full tractography method that could be implemented in routine presurgical planning for skull base surgery.METHODSA Philips MRI machine provided diffusion-weighted and anatomical sequences for 2 healthy volunteers and 2 skull base tumor patients. Tractography of the full brainstem, the cerebellum, and cranial nerves was performed using the software DSI Studio, generalized-q-sampling reconstruction, orientation distribution function (ODF) of fibers, and a quantitative anisotropy–based generalized deterministic algorithm. No ROI or extensive manual filtering of spurious fibers was used. Tractography rendering was displayed in a tridimensional space with directional color code. This approach was also tested on diffusion data from the Human Connectome Project (HCP) database.RESULTSThe brainstem, the cerebellum, and the cisternal segments of most cranial nerves were depicted in all participants. In cases of skull base tumors, the tridimensional rendering permitted the visualization of the whole anatomical environment and cranial nerve displacement, thus helping the surgical strategy.CONCLUSIONSAs opposed to classical ROI-based methods, this novel full tractography approach could enable routine enhanced surgical planning or brain imaging for skull base tumors.

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Abimanyu, Bagus, Luthfi Rusyadi, and Taufiq Taufiq. "Analisis Informasi Citra Anatomi Fase Late Artery dengan Variasi Time Scan Delay pada Pemeriksaan MSCT Abdomen." Jurnal Imejing Diagnostik (JImeD) 3, no. 1 (January 9, 2017): 213–19. http://dx.doi.org/10.31983/jimed.v3i1.3187.

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Background: MSCT Abdomen late arterial phase is a radiological examination to evaluated enhancement in hypervascular lesions, stomach, bowel, pancreas parenchyma, spleen and kidney outer cortex. All the structures get bloodsupply of the artery will show an optimal increase (Smithuis, 2014). Smithuis (2014) used time scan delay 15-20 seconds. However in the Abdomen MSCT examination in the late arterial phase of Radiology Hospital Dr. Kanujoso Djatiwibowo Balikpapan used the different time scan delay. This study aimed to determine differences in contrast enhancement with time scan delay variation of contrast media and to determine the optimal time scan delay in the examination of the Abdomen MSCT late arterial phase.Methods: The research type is quantitative experimental approach. Data are taken in October and November 2016. The research population of abdomen MSCT examination clinical intra-abdominal mass cases. Total sample are 18 people with a predetermined inclusion criteria. Time scan delay variation used are 10 seconds, 15 seconds, 20 seconds. evaluated with respondents the data is processed with statistic analysis by using different test Kruskal-Wallis followed by post hock Mann-Whitney and to get the most optimal assessment visits of mean rank the Kruskal-Wallis test.Result: The results obtained p value 0,001 (p 0,05), there are shown significant differences between time scan delay 10 seconds, 15 seconds, 20 seconds at Abdomen MSCT examination in the late arterial phase of Radiology Dr. Kanujoso Djatiwibowo Balikpapan Hospital. An optimal time scan delay on Abdomen MSCT examination late arterial phase is 10 seconds premises ROI tracking on descenden aorta. From the results of tests conducted using the Kruskal-Wallis test values mean rank at the time scan delay of 10 seconds is 84,75.Conclusison: There is a difference significant anatomical image information between the time scan delay 10 seconds, 15 seconds, 20 seconds. on MSCT Abdomen examination artery in the late phase of Radiology Dr. Kanujoso Djatiwibowo Balikpapan Hospital. assessment results are tested using the Kruskal-Wallis test followed Mann-Whitney post hock obtained p value 0.001 (p 0.05), meaning that there is a difference between the third anatomical image information with time scan delay variations. Time delay optimal scan on Abdomen MSCT examination late artery phase that time scan delay 10 seconds by tracking ROI on descenden aorta. From the results of tests conducted using the Kruskal-Wallis test values mean rank at the time scan delay of 10 seconds 84.75, 56.62 ie 15 seconds, 20 seconds, namely 22.12.

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Tumurbaatar, Batgerel, Chan-Hee Park, Jun Hee Lee, and Cheol Sang Kim. "Controls of Trajectories for Targeting of Magnetic Robotics in body." Embedded Selforganising Systems 4, no. 1 (December 7, 2017): 2–5. http://dx.doi.org/10.14464/ess41197.

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This paper presents a novel method to actively control magnetic field in a region-of-interest using three pairs electromagnetic coils system referred to here as extended distributed treatment Robotics. The developed controls of trajectories for targeting of magnetic robotics in body system contains hardware, software and magnetic Robotics/nanoscale material and the in vitro manipulation in real time. In this study, we used six identical solenoids coil placed on an XYZ-axis and the electromagnet was powered by current that can generate a high-gradient magnetic field in the desired direction. Real-time video microscopy supported by the LabVIEW vision system is integrated into the developed system for real-time monitoring. Moreover, the detection of object function is done through NI Vision Assistant, tracking function is through Math Script node in the LabVIEW simulation and ROI magnetic field actual measurement is done by the real-time magnetic sensor. The motion speed and direction of the Magnetic Robotics can also be manipulated using EMM system and Joystick controller.

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Junoh, Ahmad Kadri, Muhammad Naufal Mansor, Mohd Shafarudy Abu, Wan Zuki Azman Wan Ahmad, Wan Nur Hadani Wan Jaafar, Azhan Zamire Mukhtar, Siti Fazlina Fauzi, and Siti Haida Ismail. "Smart Surveillance System Detection Using PCA- Based Feature Extraction." Applied Mechanics and Materials 232 (November 2012): 137–41. http://dx.doi.org/10.4028/www.scientific.net/amm.232.137.

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Perception of vision and motion is a vast interdisciplinary field combining psychology, neurology, physiology, mathematics, computer science, physics, philosophy and more. The issue of the actual mechanism for the visual and computational perception of motion in the human are keep grow for the last decade. Each of the researchers is keep pursuit to find the ideal potion of a robust recognition and detection for video system. Clutches by illumination and pose variations, several compensation techniques were proposed to overcome these issues. However, were successful for face recognition in partly lightened faces and not for facial expression recognition (FER). Attempts were made to implement FER. However these were not focused for intruder face recognition/monitoring. They lack the region of interest (ROI, in this case face detection) while processing, which is crucial for environment such as in a car (a possibility of another person behind/beside the driver). Thus, an Automated Video Surveillance system is presented in this paper. The system aims at tracking an object in motion and classifying it as a human or non-human entity, which would help in subsequent human activity analysis based on PCA based feature extraction.

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Münnich, Timo, Jan Klein, Elke Hattingen, Anika Noack, Eva Herrmann, Volker Seifert, Christian Senft, and Marie-Therese Forster. "Tractography Verified by Intraoperative Magnetic Resonance Imaging and Subcortical Stimulation During Tumor Resection Near the Corticospinal Tract." Operative Neurosurgery 16, no. 2 (April 14, 2018): 197–210. http://dx.doi.org/10.1093/ons/opy062.

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Abstract BACKGROUND Tractography is a popular tool for visualizing the corticospinal tract (CST). However, results may be influenced by numerous variables, eg, the selection of seeding regions of interests (ROIs) or the chosen tracking algorithm. OBJECTIVE To compare different variable sets by correlating tractography results with intraoperative subcortical stimulation of the CST, correcting intraoperative brain shift by the use of intraoperative MRI. METHODS Seeding ROIs were created by means of motor cortex segmentation, functional MRI (fMRI), and navigated transcranial magnetic stimulation (nTMS). Based on these ROIs, tractography was run for each patient using a deterministic and a probabilistic algorithm. Tractographies were processed on pre- and postoperatively acquired data. RESULTS Using a linear mixed effects statistical model, best correlation between subcortical stimulation intensity and the distance between tractography and stimulation sites was achieved by using the segmented motor cortex as seeding ROI and applying the probabilistic algorithm on preoperatively acquired imaging sequences. Tractographies based on fMRI or nTMS results differed very little, but with enlargement of positive nTMS sites the stimulation-distance correlation of nTMS-based tractography improved. CONCLUSION Our results underline that the use of tractography demands for careful interpretation of its virtual results by considering all influencing variables.

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Chan, Shun Seng, Chockalingam Aravind Vaithilingam, and Gowthamraj Rajendran. "Cost-Saving Opportunities for Taylor’s University Daily Energy Consumption." MATEC Web of Conferences 335 (2021): 02001. http://dx.doi.org/10.1051/matecconf/202133502001.

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Solar energy is a renewable energy abundant throughout the year in a tropical weather country like Malaysia. This paper investigates the viability of using solar PV systems as a cost-saving measure to supply electricity for Taylor’s University (TU) daily energy usage. Experimental values were compared with theoretical values and analyzed in this paper. In this experiment, four photovoltaic (PV) panels connected in parallel were linked to a maximum power point tracking (MPPT) charge controller acting as a voltage regulator. A lead-acid battery was also coupled to the controller that acts as an energy storage to store the harvested solar energy from PV panels and discharge it in electricity. Temperature sensors connected to an Arduino UNO were placed at different locations on the solar panels to monitor for irregularities in the temperature of the panels. The amount of electricity produced was calculated using the data obtained. The results showed that using a larger PV system will generate much more electricity and create a high return on investment (ROI) if the solar panels absorbed sunlight under good weather conditions, thus bringing forward a potential solution to reduce TU’s electricity consumption.

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LEE, JIANN-SHU, and YI-NUNG CHUNG. "INTEGRATING EDGE DETECTION AND THRESHOLDING APPROACHES TO SEGMENTING FEMORA AND PATELLAE FROM MAGNETIC RESONANCE IMAGES." Biomedical Engineering: Applications, Basis and Communications 17, no. 01 (February 25, 2005): 1–11. http://dx.doi.org/10.4015/s1016237205000020.

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Anterior knee pain (AKP) is a common pathological condition. The most obvious problem causing knee pain is the abnormal patellar tracking mechanism. For computerized knee joint analysis, how to successfully segment the knee bones is an import issue. This paper presents a simple while effective algorithm for fully automatic femur and patella segmentation for magnetic resonance (MR) knee images through integrating edge detection and thresholding approaches. Based on consideration of computational complexity and accuracy, we develop a compound approach to segment the MR knee images. The moment preserving thresholding is first utilized to gather the bone-outline information employed to estimate the region of interest (ROI). An ROI based wavelet enhancement is proposed to restrict the contrast improvement only around the bone edges. The restriction makes both the adhesion separation of bone and surrounding tissues and the bone contour conservation become possible and avoid harsh thresholding resulting from the global based wavelet enhancement. Cooperating with the morphology operation, stable initial guess of the bone regions can be achieved. To overwhelm the main drawback of the existing edge based segmentation methods, i.e. the necessity of complicated post-processing, a new approach - FLoG is proposed to provide a feasible solution. It converts the edge detection results using LoG into a region-based format through the flow fill operation. The developed onion-growing algorithm can properly combine the initial guess of bone regions with the FLoG outputs in an efficient way. The experimental study shows our method is superior to the conventional ones in meeting the requirement of physicians. This is because our method can perform well in dealing with the tougher conditions, i.e. the partial volume and the soft tissue adhesion conditions. Because of the integration of the thresholding approach with the FLoG edge detector, our algorithm is even robust to unsatisfactory imaging conditions. Hence, our method lends itself to assisting the clinical diagnosis of knee functions.

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Ajana, M. E., H. Harroud, M. Boulmalf, and M. Elkoutbi. "FlexRFID Middleware in the Supply Chain." International Journal of Mobile Computing and Multimedia Communications 3, no. 2 (April 2011): 19–32. http://dx.doi.org/10.4018/jmcmc.2011040102.

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Radio Frequency Identification (RFID) has been used since the Second World War to identify “friend or foe” aircrafts. It has become an enabling wireless technology that is widely used in a number of application areas, such as product tracking through manufacturing and assembly, inventory control, and supply chain management (SCM). By 2006, Wal-Mart used RFID for all of its suppliers. The use of RFID in supply chain networks has allowed Wal-Mart to create value through greater visibility in its networks, higher product velocity, reduce human error and labor cost, and more efficient inventory management, which led to the achievement of Quick Response (QR) and improved Customer Relationship Management (CRM) in the supply chain. However, RFID system challenges and uncertain Return-On-Investment (ROI) must be overcome to fully achieve these objectives. This paper introduces RFID technology and its key components and concepts, and presents an RFID middleware solution called FlexRFID that achieves the maximum benefits of RFID technology independently of the interested backend applications. This paper illustrates how RFID technology is used to solve the main problems in SCM, the advantages and key issues when implementing RFID in SCM networks, and the relationship between RFID and the main SCM processes.

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Journal articles on the topic 'ROI tracking'

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