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Journal articles on the topic 'Automatic; Video; Interpretation'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Lavee, G., E. Rivlin, and M. Rudzsky. "Understanding Video Events: A Survey of Methods for Automatic Interpretation of Semantic Occurrences in Video." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 39, no. 5 (2009): 489–504. http://dx.doi.org/10.1109/tsmcc.2009.2023380.

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WITHERS, C. S. "ORTHOGONAL FUNCTIONS AND ZERNIKE POLYNOMIALS—A RANDOM VARIABLE INTERPRETATION." ANZIAM Journal 50, no. 3 (2009): 435–44. http://dx.doi.org/10.1017/s1446181109000169.

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AbstractThere are advantages in viewing orthogonal functions as functions generated by a random variable from a basis set of functions. Let Y be a random variable distributed uniformly on [0,1]. We give two ways of generating the Zernike radial polynomials with parameter l, {Zll+2n(x), n≥0}. The first is using the standard basis {xn,n≥0} and the random variable Y1/(l+1). The second is using the nonstandard basis {xl+2n,n≥0} and the random variable Y1/2. Zernike polynomials are important in the removal of lens aberrations, in characterizing video images with a small number of numbers, and in au

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Guo, Pengyu, Shaowen Ding, Hongliang Zhang, and Xiaohu Zhang. "A Real-Time Optical Tracking and Measurement Processing System for Flying Targets." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/976590.

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Optical tracking and measurement for flying targets is unlike the close range photography under a controllable observation environment, which brings extreme conditions like diverse target changes as a result of high maneuver ability and long cruising range. This paper first designed and realized a distributed image interpretation and measurement processing system to achieve resource centralized management, multisite simultaneous interpretation and adaptive estimation algorithm selection; then proposed a real-time interpretation method which contains automatic foreground detection, online targe

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Morozov, A. A., O. S. Sushkova, I. A. Kershner, and A. F. Polupanov. "Development of a Method of Terahertz Intelligent Video Surveillance Based on the Semantic Fusion of Terahertz and 3D Video Images." Information Technology and Nanotechnology, no. 2391 (2019): 134–43. http://dx.doi.org/10.18287/1613-0073-2019-2391-134-143.

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The terahertz video surveillance opens up new unique opportunities in the field of security in public places, as it allows to detect and thus to prevent usage of hidden weapons and other dangerous items. Although the first generation of terahertz video surveillance systems has already been created and is available on the security systems market, it has not yet found wide application. The main reason for this is in that the existing methods for analyzing terahertz images are not capable of providing hidden and fully-automatic recognition of weapons and other dangerous objects and can only be us

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GERICKE, LUTZ, RAJA GUMIENNY, and CHRISTOPH MEINEL. "COLLABORATECOM SPECIAL ISSUE ANALYZING DISTRIBUTED WHITEBOARD INTERACTIONS." International Journal of Cooperative Information Systems 21, no. 03 (2012): 199–220. http://dx.doi.org/10.1142/s021884301241002x.

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We present the digital whiteboard system Tele-Board, which automatically captures all interactions made on the all-digital whiteboard and thus offers possibilities for a fast interpretation of usage characteristics. Analyzing team work at whiteboards is a time-consuming and error-prone process if manual interpretation techniques are applied. In a case study, we demonstrate how to conduct and analyze whiteboard experiments with the help of our system. The study investigates the role of video compared to an audio-only connection for distributed work settings. With the simplified analysis of comm

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Tneb, Rainer, Andreas Seidl, Guido Hansen, and C. Pruett. "3-D Body Scanning - Systems, Methods and Applications for Automatic Interpretation of 3D Surface Anthropometrical Data." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 38 (2000): 844–47. http://dx.doi.org/10.1177/154193120004403844.

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Since the early beginning of the development of the 3-D digital human and ergonomics tool RAMSIS in 1988, appropriate measurement systems had been developed simultaneously. New integrated approaches and methods for human body measurement have been investigated and developed. TECMATH has developed the VITUS Pro and VITUS Smart 3-D Full Body Laser Scanner family for high precision, and adapted a 2-D video camera-based system that is simple to use and inexpensive. In the past three years, novel applications for mass customization have been developed specifically for the clothing industry. More th

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Brás, Luís M. R., Elsa F. Gomes, Margarida M. M. Ribeiro, and M. M. L. Guimarães. "Drop Distribution Determination in a Liquid-Liquid Dispersion by Image Processing." International Journal of Chemical Engineering 2009 (2009): 1–6. http://dx.doi.org/10.1155/2009/746439.

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This paper presents the implementation of an algorithm for automatic identification of drops with different sizes in monochromatic digitized frames of a liquid-liquid chemical process. These image frames were obtained at our Laboratory, using a nonintrusive process, with a digital video camera, a microscope, and an illumination setup from a dispersion of toluene in water within a transparent mixing vessel. In this implementation, we propose a two-phase approach, using a Hough transform that automatically identifies drops in images of the chemical process. This work is a promising starting poin

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Smolyakov, P. N. "Liability of Legal Entities for Offenses Recorded by Special Technical Devices." Actual Problems of Russian Law 1, no. 12 (2020): 11–16. http://dx.doi.org/10.17803/1994-1471.2019.109.12.011-016.

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The article is devoted to the exemption of legal entities from liability for administrative offenses recorded by special technical devices operating in an automatic mode and having functions of photo and film shooting, video recording, or by means of photo and film shooting, video recording. It is noted that the existing regulation in the Administrative Code of the Russian Federation in the interpretation of the highest court and other courts makes such liability ephemeral, allowing to arbitrarily shift it, for example, onto natural persons, e.i. drivers of vehicles belonging to legal entities

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Kang, Hyung W., and Sung Yong Shin. "Creating Walk-Through Images from a Video Sequence of a Dynamic Scene." Presence: Teleoperators and Virtual Environments 13, no. 6 (2004): 638–55. http://dx.doi.org/10.1162/1054746043280556.

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Tour into the picture (TIP), proposed by Horry et al. (Horry, Anjyo, & Arai, 1997, ACM SIGGRAPH '97 Conference Proceedings, 225–232) is a method for generating a sequence of walk-through images from a single reference image. By navigating a 3D scene model constructed from the image, TIP provides convincing 3D effects. This paper presents a comprehensive scheme for creating walk-through images from a video sequence by generalizing the idea of TIP. To address various problems in dealing with a video sequence rather than a single image, the proposed scheme is designed to have the following fe

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Xiu, Hongling, and Fengyun Yang. "Batch Processing of Remote Sensing Image Mosaic based on Python." International Journal of Online Engineering (iJOE) 14, no. 09 (2018): 208. http://dx.doi.org/10.3991/ijoe.v14i09.9226.

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In the process of remote sensing image processing, analysis and interpretation, it is usually necessary to combine several local images into a complete image. Aiming at the shortcoming of long and complicated process of conventional semi-automatic video stitching. In this paper, using the splicing method of pixels, based on the Python interface of ArcGIS 10.1 platform, the idea of programming language is introduced and batch mosaic of remote sensing images is realized. Through the comparison with the image processing software, it is found that this method can shorten the time of image mosaic a

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Mu, Yaxin, Xiaojuan Zhang, Wupeng Xie, and Yaoxin Zheng. "Automatic Detection of Near-Surface Targets for Unmanned Aerial Vehicle (UAV) Magnetic Survey." Remote Sensing 12, no. 3 (2020): 452. http://dx.doi.org/10.3390/rs12030452.

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Great progress has been made in the integration of Unmanned Aerial Vehicle (UAV) magnetic measurement systems, but the interpretation of UAV magnetic data is facing serious challenges. This paper presents a complete workflow for the detection of the subsurface objects, like Unexploded Ordnance (UXO), by the UAV-borne magnetic survey. The elimination of interference field generated by the drone and an improved Euler deconvolution are emphasized. The quality of UAV magnetic data is limited by the UAV interference field. A compensation method based on the signal correlation is proposed to remove

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Petre, Raluca-Diana, and Titus Zaharia. "3D Model-Based Semantic Categorization of Still Image 2D Objects." International Journal of Multimedia Data Engineering and Management 2, no. 4 (2011): 19–37. http://dx.doi.org/10.4018/jmdem.2011100102.

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Automatic classification and interpretation of objects present in 2D images is a key issue for various computer vision applications. In particular, when considering image/video, indexing, and retrieval applications, automatically labeling in a semantically pertinent manner/huge multimedia databases still remains a challenge. This paper examines the issue of still image object categorization. The objective is to associate semantic labels to the 2D objects present in natural images. The principle of the proposed approach consists of exploiting categorized 3D model repositories to identify unknow

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Tang, Ziyang, Xiang Liu, Hanlin Chen, Joseph Hupy, and Baijian Yang. "Deep Learning Based Wildfire Event Object Detection from 4K Aerial Images Acquired by UAS." AI 1, no. 2 (2020): 166–79. http://dx.doi.org/10.3390/ai1020010.

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Unmanned Aerial Systems, hereafter referred to as UAS, are of great use in hazard events such as wildfire due to their ability to provide high-resolution video imagery over areas deemed too dangerous for manned aircraft and ground crews. This aerial perspective allows for identification of ground-based hazards such as spot fires and fire lines, and to communicate this information with fire fighting crews. Current technology relies on visual interpretation of UAS imagery, with little to no computer-assisted automatic detection. With the help of big labeled data and the significant increase of c

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López, Juan Pedro, Marta Bosch-Baliarda, Carlos Alberto Martín, et al. "Design and development of sign language questionnaires based on video and web interfaces." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 33, no. 4 (2019): 429–41. http://dx.doi.org/10.1017/s0890060419000374.

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AbstractConventional tests with written information used for the evaluation of sign language (SL) comprehension introduce distortions due to the translation process. This fact affects the results and conclusions drawn and, for that reason, it is necessary to design and implement the same language interpreter-independent evaluation tools. Novel web technologies facilitate the design of web interfaces that support online, multiple-choice questionnaires, while exploiting the storage of tracking data as a source of information about user interaction. This paper proposes an online, multiple-choice

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Han, Dongyeob, Suk Bae Lee, Mihwa Song, and Jun Sang Cho. "Change Detection in Unmanned Aerial Vehicle Images for Progress Monitoring of Road Construction." Buildings 11, no. 4 (2021): 150. http://dx.doi.org/10.3390/buildings11040150.

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Currently, unmanned aerial vehicles are increasingly being used in various construction projects such as housing developments, road construction, and bridge maintenance. If a drone is used at a road construction site, elevation information and orthoimages can be generated to acquire the construction status quantitatively. However, the detection of detailed changes in the site owing to construction depends on visual video interpretation. This study develops a method for automatic detection of the construction area using multitemporal images and a deep learning method. First, a deep learning mod

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Gerdes, Martin, Frode Gallefoss, and Rune Werner Fensli. "The EU project “United4Health”: Results and experiences from automatic health status assessment in a Norwegian telemedicine trial system." Journal of Telemedicine and Telecare 25, no. 1 (2017): 46–53. http://dx.doi.org/10.1177/1357633x17735558.

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Introduction Patients with chronic obstructive pulmonary disease require help in daily life situations to increase their individual perception of security, especially under worsened medical conditions. Unnecessary hospital (re-)admissions and home visits by doctors or nurses shall be avoided. This study evaluates the results from a two-year telemedicine field trial for automatic health status assessment based on remote monitoring and analysis of a long time series of vital signs data from patients at home over periods of weeks or months. Methods After discharge from hospital treatment for acut

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Vishaka Gayathri, D., Shrutee Shree, Taru Jain, and K. Sornalakshmi. "Real Time System for Human Identification and Tracking from Surveillance Videos." International Journal of Engineering & Technology 7, no. 3.12 (2018): 244. http://dx.doi.org/10.14419/ijet.v7i3.12.16034.

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The need for intelligent surveillance systems has raised the concerns of security. A viable system with automated methods for person identification to detect, track and recognize persons in real time is required. The traditional detection techniques have not been able to analyze such a huge amount of live video generated in real-time. So, there is a necessity for live streaming video analytics which includes processing and analyzing large scale visual data such as images or videos to find content that are useful for interpretation. In this work, an automated surveillance system for real-time d

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Rezaei, Behnaz, Yiorgos Christakis, Bryan Ho, et al. "Target-Specific Action Classification for Automated Assessment of Human Motor Behavior from Video." Sensors 19, no. 19 (2019): 4266. http://dx.doi.org/10.3390/s19194266.

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Objective monitoring and assessment of human motor behavior can improve the diagnosis and management of several medical conditions. Over the past decade, significant advances have been made in the use of wearable technology for continuously monitoring human motor behavior in free-living conditions. However, wearable technology remains ill-suited for applications which require monitoring and interpretation of complex motor behaviors (e.g., involving interactions with the environment). Recent advances in computer vision and deep learning have opened up new possibilities for extracting informatio

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Hennessy, S. J., L. B. Wong, D. B. Yeates, and I. F. Miller. "Automated measurement of ciliary beat frequency." Journal of Applied Physiology 60, no. 6 (1986): 2109–13. http://dx.doi.org/10.1152/jappl.1986.60.6.2109.

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Measurements of ciliary beat frequency using video images are dependent on observer interpretation. To obtain objective estimates of ciliary beat frequency from video-image sequences, a computer-based method was developed. Regions of interest of video-image sequences were selected and digitized. Variations in numerical values representing light intensity resulting from cilia beating were extracted and analyzed using autocorrelation techniques. The ciliary beat frequencies obtained for 14 in vitro experiments on ciliated cells or epithelium from the frog palate (Rana catesbeiana) over the range

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Jani, Kuntesh Ketan, and Rajeev Srivastava. "A Survey on Medical Image Analysis in Capsule Endoscopy." Current Medical Imaging Formerly Current Medical Imaging Reviews 15, no. 7 (2019): 622–36. http://dx.doi.org/10.2174/1573405614666181102152434.

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Background and Objective: Capsule Endoscopy (CE) is a non-invasive, patient-friendly alternative to conventional endoscopy procedure. However, CE produces 6 to 8 hrs long video posing a tedious challenge to a gastroenterologist for abnormality detection. Major challenges to an expert are lengthy videos, need of constant concentration and subjectivity of the abnormality. To address these challenges along with high diagnostic accuracy, design and development of automated abnormality detection system is a must. Machine learning and computer vision techniques are devised to develop such automated

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Gong, Jie, and Carlos H. Caldas. "Computer Vision-Based Video Interpretation Model for Automated Productivity Analysis of Construction Operations." Journal of Computing in Civil Engineering 24, no. 3 (2010): 252–63. http://dx.doi.org/10.1061/(asce)cp.1943-5487.0000027.

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Díaz-Vilariño, L., J. Martínez-Sánchez, S. Lagüela, J. Armesto, and K. Khoshelham. "Door recognition in cluttered building interiors using imagery and lidar data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5 (June 6, 2014): 203–9. http://dx.doi.org/10.5194/isprsarchives-xl-5-203-2014.

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Building indoors reconstruction is an active research topic due to the importance of the wide range of applications to which they can be subjected, from architecture and furniture design, to movies and video games editing, or even crime scene investigation. Among the constructive elements defining the inside of a building, doors are important entities in applications like routing and navigation, and their automated recognition is advantageous e.g. in case of large multi-storey buildings with many office rooms. The inherent complexity of the automation of the recognition process is increased by

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Huang, Mu-Shiang, Chi-Shiang Wang, Jung-Hsien Chiang, Ping-Yen Liu, and Wei-Chuan Tsai. "Automated Recognition of Regional Wall Motion Abnormalities Through Deep Neural Network Interpretation of Transthoracic Echocardiography." Circulation 142, no. 16 (2020): 1510–20. http://dx.doi.org/10.1161/circulationaha.120.047530.

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Background: Automated interpretation of echocardiography by deep neural networks could support clinical reporting and improve efficiency. Whereas previous studies have evaluated spatial relationships using still frame images, we aimed to train and test a deep neural network for video analysis by combining spatial and temporal information, to automate the recognition of left ventricular regional wall motion abnormalities. Methods: We collected a series of transthoracic echocardiography examinations performed between July 2017 and April 2018 in 2 tertiary care hospitals. Regional wall abnormalit

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Kolls, Brad J., and Brian E. Mace. "A practical method for determining automated EEG interpretation software performance on continuous Video-EEG monitoring data." Informatics in Medicine Unlocked 23 (2021): 100548. http://dx.doi.org/10.1016/j.imu.2021.100548.

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Наумов, А., Andrey Naumov, Д. Юдин, D. Yudin, А. Долженко, and Aleksandr Dolzhenko. "IMPROVING THE TECHNOLOGY OF CONSTRUCTION AND TECHNICAL EXPERTISE USING A HARDWARE AND SOFTWARE COMPLEX OF AUTOMATED INSPECTION." Bulletin of Belgorod State Technological University named after. V. G. Shukhov 4, no. 4 (2019): 61–69. http://dx.doi.org/10.34031/article_5cb824d26344e7.45899508.

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In the construction and technical expertise of buildings, inspection is an important and crucial part in the conclusions about the technical condition of the object. It is carried out visually and instrumentally with the interpretation of results by subjective expert methods. The current performance standard of construction and technical inspection has several disadvantages: essential schematics of collection algorithms, simplified diagnostics and coarsening of the analysis of field research results for geometrically extended or constructively complex real estate objects, which are caused by n

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Cree, Christopher, Emily Carter, Heng Wang, Changki Mo, and John Miller. "Tracking Robot Location for Non-Destructive Evaluation of Double-Shell Tanks." Applied Sciences 10, no. 20 (2020): 7318. http://dx.doi.org/10.3390/app10207318.

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(1) Background: Non-destructive evaluation of double-shell nuclear-waste storage tanks at the U.S. Department of Energy’s Hanford site requires a robot to navigate a network of air slots in the confined space between primary and secondary tanks. Situational awareness, data collection, and data interpretation require continuous tracking of the robot’s location. (2) Methods: Robot location is continuously monitored using video image analysis for short distances and laser ranging for absolute location. (3) Results: The technique was demonstrated in our laboratory using a mockup of air slot and ro

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Khan, Muhammad Arsalan, Wim Ectors, Tom Bellemans, Davy Janssens, and Geert Wets. "Unmanned Aerial Vehicle–Based Traffic Analysis: Methodological Framework for Automated Multivehicle Trajectory Extraction." Transportation Research Record: Journal of the Transportation Research Board 2626, no. 1 (2017): 25–33. http://dx.doi.org/10.3141/2626-04.

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Unmanned aerial vehicles (UAVs), commonly referred to as drones, are one of the most dynamic and multidimensional emerging technologies of the modern era. This technology has recently found multiple potential applications within the transportation field, ranging from traffic surveillance applications to traffic network analysis. To conduct a UAV-based traffic study, extremely diligent planning and execution are required followed by an optimal data analysis and interpretation procedure. In this study, however, the main focus was on the processing and analysis of UAV-acquired traffic footage. A

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Borwarnginn, Punyanuch, Worapan Kusakunniran, Parintorn Pooyoi, and Jason H. Haga. "Segmenting Snow Scene from CCTV using Deep Learning Approach." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 13, no. 2 (2020): 151–59. http://dx.doi.org/10.37936/ecti-cit.2019132.216323.

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Recently, data from many sensors has been used in a disaster monitoring of things, such as river wa- ter levels, rainfall levels, and snowfall levels. These types of numeric data can be straightforwardly used in a further analysis. In contrast, data from CCTV cameras (i.e. images and/or videos) cannot be easily interpreted for users in an automatic way. In a tra- ditional way, it is only provided to users for a visual- ization without any meaningful interpretation. Users must rely on their own expertise and experience to interpret such visual information. Thus, this paper proposes the CNN-base

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Mohamed, Mohamed Gomaa, and Nicolas Saunier. "Behavior Analysis Using a Multilevel Motion Pattern Learning Framework." Transportation Research Record: Journal of the Transportation Research Board 2528, no. 1 (2015): 116–27. http://dx.doi.org/10.3141/2528-13.

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The increasing availability of video data, through existing traffic cameras or dedicated field data collection, and the development of computer vision techniques pave the way for the collection of massive data sets about the microscopic behavior of road users. Analysis of such data sets helps in understanding normal road user behavior and can be used for realistic prediction of motion and computation of surrogate safety indicators. A multilevel motion pattern learning framework was developed to enable automated scene interpretation, anomalous behavior detection, and surrogate safety analysis.

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McGuire, Patrick Charles, Jens Ormö, Enrique Díaz Martínez, et al. "The Cyborg Astrobiologist: first field experience." International Journal of Astrobiology 3, no. 3 (2004): 189–207. http://dx.doi.org/10.1017/s147355040500220x.

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We present results from the first geological field tests of the ‘Cyborg Astrobiologist’, which is a wearable computer and video camcorder system that we are using to test and train a computer-vision system towards having some of the autonomous decision-making capabilities of a field-geologist and field-astrobiologist. The Cyborg Astrobiologist platform has thus far been used for testing and development of the following algorithms and systems: robotic acquisition of quasi-mosaics of images; real-time image segmentation; and real-time determination of interesting points in the image mosaics. The

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Marres, Noortje. "For a situational analytics: An interpretative methodology for the study of situations in computational settings." Big Data & Society 7, no. 2 (2020): 205395172094957. http://dx.doi.org/10.1177/2053951720949571.

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This article introduces an interpretative approach to the analysis of situations in computational settings called situational analytics. I outline the theoretical and methodological underpinnings of this approach, which is still under development, and show how it can be used to surface situations from large data sets derived from online platforms such as YouTube. Situational analytics extends to computationally-mediated settings a qualitative methodology developed by Adele Clarke, Situational Analysis (2005), which uses data mapping to detect heterogeneous entities in fieldwork data to determi

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Tataris, G., N. Soulakellis, and K. Chaidas. "MULTITEMPORAL 3D MAPPING OF POST-EARTHQUAKE RECOVERY PHASE WITH UAS: CASE STUDY VRISA, LESVOS, GREECE." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences VI-3/W1-2020 (November 17, 2020): 123–30. http://dx.doi.org/10.5194/isprs-annals-vi-3-w1-2020-123-2020.

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Abstract. The recovery phase of an earthquake-affected settlement is a time-consuming and complex process that requires monitoring, which is now possible using UAS. The purpose of this paper is to present the methodology followed and the results obtained by the exploitation of UAS for rapid multitemporal 3D mapping during the recovery phase of Vrisa traditional settlement, Lesvos island, Greece, which was highly damaged by the earthquake (Mw=6.3) on 12th June 2017. More analytically, three (3) flight campaigns covering the period July 2017 – May 2020 took place by means of an UAS for collectin

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Brea Castro, Millán. "Didactic methodology in professional e-sport training. An international experience in Brawl Stars (Metodología didáctica en entrenamiento profesional de e-sport. Una experiencia internacional en Brawl Stars)." Retos, no. 41 (December 31, 2020): 247–55. http://dx.doi.org/10.47197/retos.v0i41.83225.

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The impact of eSports today is undeniable. Millions of connected players, international competitions with succulent economic awards, diversity of platforms to participate or track the competitions. A new system of youth socialization, channelled through video games, in which the competition requires a complete sport training. This article describes the methodological strategies for teaching and learning eSports from a semi-professional team. The analysed categories are: training type and schedule, used tools and typology of feedback carried out for the automation of playing behaviours. The res

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van der Spek, Alex, and Alix Thomas. "Neural-Net Identification of Flow Regime With Band Spectra of Flow-Generated Sound." SPE Reservoir Evaluation & Engineering 2, no. 06 (1999): 489–98. http://dx.doi.org/10.2118/59067-pa.

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Summary Multiphase production log interpretation requires that the flow regime along hole in the wellbore is known. Flow regime is the cased-hole analog of lithology. Knowledge of the flow regime will help to interpret tool signals, will help to evaluate the flow rate on a per phase basis, and will reduce post-processing load. The flow regime can be classified correctly by a neural net in up to 87% of all cases using 1/3 octave band spectra of flow-generated sound plus the pipe inclination angle. Without the inclination an 88% correct classification can be achieved. A neural net trained on com

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Cantin-Garside, Kristine, Rupa S. Valdez, Maury A. Nussbaum, et al. "Exploring Challenges of Monitoring Technology and Self-Injurious Behavior in Autism Spectrum Disorder." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 620–21. http://dx.doi.org/10.1177/1541931218621141.

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Self-injurious behavior (SIB), such as head banging or self-hitting, is considered one of the most dangerous characteristics of autism spectrum disorder (ASD) (Mahatmya, Zobel, & Valdovinos, 2008). Clinicians traditionally rely on structured observation, which can be time-consuming and invasive. Recent technological developments in motion tracking may decrease these burdens. For example, accelerometers in smart watches can gather movement information, which could be automatically classified to detect and predict events associated with SIB using machine learning algorithms. While such syste

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Veluchamy, S., L. R. Karlmarx, and K. Michael Mahesh. "Detection and Localization of Abnormalities in Surveillance Video Using Timerider-Based Neural Network." Computer Journal, March 19, 2021. http://dx.doi.org/10.1093/comjnl/bxab002.

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Abstract Automatic anomaly detection in surveillance videos is a trending research domain, which assures the detection of the anomalies effectively, relieves the time-consumed by the manual interpretation methods without the requirement of the domain knowledge about the anomalous object. Accordingly, this research work proposes an effective anomaly detection approach, named, TimeRide Neural network (TimeRideNN), by modifying the standard RideNN using the Taylor series such that an extra group of rider, named as timerider, is included in the standard rider optimization algorithm. Initially, the

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Ahouandjinou, Arnaud, Eugène C. Ezin, and Cina Motamed. "Temporal and Hierarchical HMM for Activity Recognition Applied in Visual Medical Monitoring using a Multi-Camera System." Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées Volume 21 - 2015 - Special... (August 30, 2015). http://dx.doi.org/10.46298/arima.1999.

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International audience We address in this paper an improved medical monitoring system through an automatic recognition of human activity in Intensive Care Units (ICUs). A multi camera vision system approach is proposed to collect video sequence for automatic analysis and interpretation of the scene. The latter is performed using Hidden Markov Model (HMM) with explicit state duration combine at the management of the hierarchical structure of the scenario. Significant experiments are carried out on the proposed monitoring system in a hospital's cardiology section in order to prove the need for c

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Ortiz de Gortari, Angelica B., and Jayne Gackenbach. "Game Transfer Phenomena and Problematic Interactive Media Use: Dispositional and Media Habit Factors." Frontiers in Psychology 12 (April 22, 2021). http://dx.doi.org/10.3389/fpsyg.2021.585547.

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The study of the effects of interactive media has mainly focused on dysregulated behaviors, the conceptualization of which is supported by the paradigms of addiction. Research into Game Transfer Phenomena (GTP) examines the interplay between video game features, events while playing, and the manipulation of hardware, which can lead to sensory-perceptual and cognitive intrusions (e.g., hallucinations and recurrent thoughts) and self-agency transient changes (e.g., automatic behaviors) related to video games. GTP can influence the interpretation of stimuli and everyday interactions and, in contr

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Burwell, Catherine. "New(s) Readers: Multimodal Meaning-Making in AJ+ Captioned Video." M/C Journal 20, no. 3 (2017). http://dx.doi.org/10.5204/mcj.1241.

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IntroductionIn 2013, Facebook introduced autoplay video into its newsfeed. In order not to produce sound disruptive to hearing users, videos were muted until a user clicked on them to enable audio. This move, recognised as a competitive response to the popularity of video-sharing sites like YouTube, has generated significant changes to the aesthetics, form, and modalities of online video. Many video producers have incorporated captions into their videos as a means of attracting and maintaining user attention. Of course, captions are not simply a replacement or translation of sound, but have in

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Huang, M. S., and M. R. Tsai. "4942Automated recognition of regional wall motion abnormalities by deep neural network interpretation of echocardiography." European Heart Journal 40, Supplement_1 (2019). http://dx.doi.org/10.1093/eurheartj/ehz746.0012.

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Abstract Background The deep neural network assisted in automated echocardiography interpretation joint to cardiologist final confirmation has now been gradually emerging. There were applications applied in echocardiography views classification, chamber size and myocardium mass evaluation, and certain disease detections already published. Our aim, instead of frame-by-frame “image-level” interpretation in previous studies, is to apply deep neural network in echocardiography temporal relationship analysis – “video-level” – and applied in automated left ventricle myocardium regional wall motion a

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Lai, Derek. "Public Video Surveillance by the State: Policy, Privacy Legislation, and the Charter." Alberta Law Review, December 30, 2015. http://dx.doi.org/10.29173/alr379.

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This article explores the growing phenomenon of public video surveillance and how the law should protect an individual's right to privacy while providing for effective law enforcement. The author considers the positive and negative effects of surveillance and recent technological advancements that currently challenge courts, legislatures, and police forces. Canadian case studies from Kelowna and Edmonton are utilized to examine the role of federal and provincial privacy legislation, while the Supreme Court of Canada's evolving interpretation of s. 8 of the Charter is canvassed through an exami

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Di Vece, D., F. Laumer, M. Schwyzer, et al. "Artificial intelligence in echocardiography diagnostics – detection of takotsubo syndrome." European Heart Journal 41, Supplement_2 (2020). http://dx.doi.org/10.1093/ehjci/ehaa946.1221.

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Abstract Background Machine learning allows classifying diseases based only on raw echocardiographic imaging data and is therefore a landmark in the development of computer-assisted decision support systems in echocardiography. Purpose The present study sought to determine the value of deep (machine) learning systems for automatic discrimination of takotsubo syndrome and acute myocardial infarction. Methods Apical 2- and 4-chamber echocardiographic views of 110 patients with takotsubo syndrome and 110 patients with acute myocardial infarction were used in the development, training and validati

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George, Jonathan K., Cesare Soci, Mario Miscuglio, and Volker J. Sorger. "Symmetry perception with spiking neural networks." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-85232-3.

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AbstractMirror symmetry is an abundant feature in both nature and technology. Its successful detection is critical for perception procedures based on visual stimuli and requires organizational processes. Neuromorphic computing, utilizing brain-mimicked networks, could be a technology-solution providing such perceptual organization functionality, and furthermore has made tremendous advances in computing efficiency by applying a spiking model of information. Spiking models inherently maximize efficiency in noisy environments by placing the energy of the signal in a minimal time. However, many ne

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Lavanchy, Joël L., Joel Zindel, Kadir Kirtac, et al. "Automation of surgical skill assessment using a three-stage machine learning algorithm." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-84295-6.

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AbstractSurgical skills are associated with clinical outcomes. To improve surgical skills and thereby reduce adverse outcomes, continuous surgical training and feedback is required. Currently, assessment of surgical skills is a manual and time-consuming process which is prone to subjective interpretation. This study aims to automate surgical skill assessment in laparoscopic cholecystectomy videos using machine learning algorithms. To address this, a three-stage machine learning method is proposed: first, a Convolutional Neural Network was trained to identify and localize surgical instruments.

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Kainz, Bernhard, Mattias P. Heinrich, Antonios Makropoulos, et al. "Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning." npj Digital Medicine 4, no. 1 (2021). http://dx.doi.org/10.1038/s41746-021-00503-7.

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AbstractDeep vein thrombosis (DVT) is a blood clot most commonly found in the leg, which can lead to fatal pulmonary embolism (PE). Compression ultrasound of the legs is the diagnostic gold standard, leading to a definitive diagnosis. However, many patients with possible symptoms are not found to have a DVT, resulting in long referral waiting times for patients and a large clinical burden for specialists. Thus, diagnosis at the point of care by non-specialists is desired. We collect images in a pre-clinical study and investigate a deep learning approach for the automatic interpretation of comp

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Jones, Steve. "Seeing Sound, Hearing Image." M/C Journal 2, no. 4 (1999). http://dx.doi.org/10.5204/mcj.1763.

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“As the old technologies become automatic and invisible, we find ourselves more concerned with fighting or embracing what’s new”—Dennis Baron, From Pencils to Pixels: The Stage of Literacy Technologies Popular music is firmly rooted within realist practice, or what has been called the "culture of authenticity" associated with modernism. As Lawrence Grossberg notes, the accelleration of the rate of change in modern life caused, in post-war youth culture, an identity crisis or "lived contradiction" that gave rock (particularly) and popular music (generally) a peculiar position in regard to notio

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Campbell, Sian Petronella. "On the Record: Time and The Self as Data in Contemporary Autofiction." M/C Journal 22, no. 6 (2019). http://dx.doi.org/10.5204/mcj.1604.

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In January of this year, artist Christian Marclay’s 24-hour video installation The Clock came to Melbourne. As Ben Lerner explains in 10:04, the autofictional novel Lerner published in 2014, The Clock by Christian Marclay “is a clock: it is a twenty-four hour montage of thousands of scenes from movies and a few from TV edited together so as to be shown in real time; each scene indicates the time with a shot of a timepiece or its mention in dialogue, time in and outside of the film is synchronized” (52). I went to see The Clock at ACMI several times, with friends and alone, in the early morning

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Ellis, Katie, Mike Kent, and Gwyneth Peaty. "Captioned Recorded Lectures as a Mainstream Learning Tool." M/C Journal 20, no. 3 (2017). http://dx.doi.org/10.5204/mcj.1262.

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In Australian universities, many courses provide lecture notes as a standard learning resource; however, captions and transcripts of these lectures are not usually provided unless requested by a student through dedicated disability support officers (Worthington). As a result, to date their use has been limited. However, while the requirement for—and benefits of—captioned online lectures for students with disabilities is widely recognised, these captions or transcripts might also represent further opportunity for a personalised approach to learning for the mainstream student population (Podszeb

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Chesher, Chris. "Mining Robotics and Media Change." M/C Journal 16, no. 2 (2013). http://dx.doi.org/10.5204/mcj.626.

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Introduction Almost all industries in Australia today have adopted digital media in some way. However, uses in large scale activities such as mining may seem to be different from others. This article looks at mining practices with a media studies approach, and concludes that, just as many other industries, mining and media have converged. Many Australian mine sites are adopting new media for communication and control to manage communication, explore for ore bodies, simulate forces, automate drilling, keep records, and make transport and command robotic. Beyond sharing similar digital devices f

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Melchior, Angelika. "Tag & Trace Marketing." M/C Journal 8, no. 4 (2005). http://dx.doi.org/10.5204/mcj.2385.

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   The use of RFID (radio frequency identification), also called “smart tags”, is on the rise in the retail industry. In short, RFID are tiny microchips using short range radio signals to emit information and can be used to tag goods, buildings, cars, pets, people etc. Unlike bar-code scanners, which must be held directly in front of the item being scanned, one of the benefits of RFID tags is that they can be scanned from a distance. It is expected that RFID will eventually replace the bar code and its use is likely to save companies like Wal-Mart, Procter & Gamble and Gi

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