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Artículos de revistas sobre el tema "Stereo baseline"

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Publicado: 10 de marzo de 2023

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1

Sumetheeprasit, Borwonpob, Ricardo Rosales Martinez, Hannibal Paul, Robert Ladig y Kazuhiro Shimonomura. "Variable Baseline and Flexible Configuration Stereo Vision Using Two Aerial Robots". Sensors 23, n.º 3 (18 de enero de 2023): 1134. http://dx.doi.org/10.3390/s23031134.

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In this work, a new method for aerial robot remote sensing using stereo vision is proposed. A variable baseline and flexible configuration stereo setup is achieved by separating the left camera and right camera on two separate quadrotor aerial robots. Monocular cameras, one on each aerial robot, are used as a stereo pair, allowing independent adjustment of the pose of the stereo pair. In contrast to conventional stereo vision where two cameras are fixed, having a flexible configuration system allows a large degree of independence in changing the configuration in accordance with various kinds of applications. Larger baselines can be used for stereo vision of farther away targets while using a vertical stereo configuration in tasks where there would be a loss of horizontal overlap caused by a lack of suitable horizontal configuration. Additionally, a method for the practical use of variable baseline stereo vision is introduced, combining multiple point clouds from multiple stereo baselines. Issues from using an inappropriate baseline, such as estimation error induced by insufficient baseline, and occlusions from using too large a baseline can be avoided with this solution.

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2

Okutomi, M. y T. Kanade. "A multiple-baseline stereo". IEEE Transactions on Pattern Analysis and Machine Intelligence 15, n.º 4 (abril de 1993): 353–63. http://dx.doi.org/10.1109/34.206955.

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3

Elias, Rimon. "Enhancing Sensor Measurements throughWide Baseline Stereo Images". ELCVIA Electronic Letters on Computer Vision and Image Analysis 7, n.º 3 (3 de diciembre de 2008): 36. http://dx.doi.org/10.5565/rev/elcvia.222.

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4

Dazhi, Zhang, Wang Yongtao y Tao Wenbing. "Epipolar Geometry Estimation for Wide Baseline Stereo". International Journal of Engineering and Manufacturing 2, n.º 3 (29 de junio de 2012): 38–45. http://dx.doi.org/10.5815/ijem.2012.03.06.

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5

Zafeiriou, Stefanos, Mark F. Hansen, Gary A. Atkinson, Maria Petrou y Melvyn L. Smith. "Baseline face recognition using photometric stereo data". Procedia Computer Science 2 (2010): 20–25. http://dx.doi.org/10.1016/j.procs.2010.11.004.

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6

Olson, Clark F. y Habib Abi-Rached. "Wide-baseline stereo vision for terrain mapping". Machine Vision and Applications 21, n.º 5 (6 de febrero de 2009): 713–25. http://dx.doi.org/10.1007/s00138-009-0188-9.

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7

Igual, L., J. Preciozzi, L. Garrido, A. Almansa, V. Caselles y B. Rougé. "Automatic low baseline stereo in urban areas". Inverse Problems & Imaging 1, n.º 2 (2007): 319–48. http://dx.doi.org/10.3934/ipi.2007.1.319.

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8

Seo, Beom-Su, Byungjae Park y Hoon Choi. "Sensing Range Extension for Short-Baseline Stereo Camera Using Monocular Depth Estimation". Sensors 22, n.º 12 (18 de junio de 2022): 4605. http://dx.doi.org/10.3390/s22124605.

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This paper proposes a method to extend a sensing range of a short-baseline stereo camera (SBSC). The proposed method combines a stereo depth and a monocular depth estimated by a convolutional neural network-based monocular depth estimation (MDE). To combine a stereo depth and a monocular depth, the proposed method estimates a scale factor of a monocular depth using stereo depth–mono depth pairs and then combines the two depths. Another advantage of the proposed method is that the trained MDE model may be utilized for different environments without retraining. The performance of the proposed method is verified qualitatively and quantitatively using the directly collected and open datasets.

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9

Kaczmarek, Adam L. "3D Vision System for a Robotic Arm Based on Equal Baseline Camera Array". Journal of Intelligent & Robotic Systems 99, n.º 1 (4 de diciembre de 2019): 13–28. http://dx.doi.org/10.1007/s10846-019-01117-8.

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AbstractThis paper presents a lightweight 3D vision system called Equal Baseline Camera Array (EBCA). EBCA can work in different light conditions and it can be applied for measuring large range of distances. The system is a useful alternative to other known distance measuring devices such as structured-light 3D scanners, time-of-flight cameras, Light Detection and Ranging (LIDAR) devices and structure from motion techniques. EBCA can be mounted on a robotic arm without putting significant load on its construction. EBCA consists of a central camera and a ring of side cameras. The system uses stereo matching algorithms to acquire disparity maps and depth maps similarly as in case of using stereo cameras. This paper introduces methods of adapting stereo matching algorithms designed for stereo cameras to EBCA. The paper also presents the analysis of local, semi-global and global stereo matching algorithms in the context of the EBCA usage. Experiments show that, on average, results obtained from EBCA contain 37.49% less errors than the results acquired from a single stereo camera used in the same conditions.

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10

Li, Jing, Hong Zhao, Zigang Li, Feifei Gu, Zixin Zhao, Yueyang Ma y Meiqi Fang. "A long baseline global stereo matching based upon short baseline estimation". Measurement Science and Technology 29, n.º 5 (23 de marzo de 2018): 055201. http://dx.doi.org/10.1088/1361-6501/aab079.

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11

Kaczmarek, Adam L. y Bernhard Blaschitz. "Equal Baseline Camera Array—Calibration, Testbed and Applications". Applied Sciences 11, n.º 18 (12 de septiembre de 2021): 8464. http://dx.doi.org/10.3390/app11188464.

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This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative to other 3D imaging equipment such as Structured-light 3D scanners or Light Detection and Ranging (LIDAR). The considered kinds of arrays are called Equal Baseline Camera Array (EBCA). This paper presents a novel approach to calibrating the array based on the use of self-calibration methods. This paper also introduces a testbed which makes it possible to develop new algorithms for obtaining 3D data from images taken by the array. The testbed was released under open-source. Moreover, this paper shows new results of using these arrays with different stereo matching algorithms including an algorithm based on a convolutional neural network and deep learning technology.

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12

Zhang, Fan, Xian Feng Huang, Xiao Zhi Qu, Jian Wang, Jian Ping Pan y Deng Feng Cheng. "Power Line Measurement Method Based on Vertical Baseline Stereo Camera". Advanced Materials Research 614-615 (diciembre de 2012): 980–87. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.980.

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Conducting regular inspections and measurements of power lines is an important way to ensure the stability and security of transmission line. For the problem of being poor reliability, poor flexibility and high cost, a power line measurement method based on vertical baseline photography is proposed and studied: Line patrol officers use portable vertical baseline stereo camera shooting in the outdoor field, and measure accurately in the stereo image taken in or after patrol. This paper describes the system design and technical methods, and analyzes the key technologies in the system calibration and measurement, and uses several sets of experiments to prove the accuracy and feasibility of this method.

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13

JIANG, WEI, SHIGEKI SUGIMOTO y MASATOSHI OKUTOMI. "PANORAMIC 3D RECONSTRUCTION USING STEREO MULTI-PERSPECTIVE PANORAMA". International Journal of Pattern Recognition and Artificial Intelligence 24, n.º 06 (septiembre de 2010): 867–96. http://dx.doi.org/10.1142/s0218001410008226.

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In this paper, we present a novel approach to imaging a panoramic (360°) environment and computing its dense depth map. Our approach adopts a multi-baseline stereo strategy using a set of multi-perspective panoramas where large baseline lengths are available. We design two image acquisition rigs for capturing such multi-perspective panoramas. The first one is composed of two parallel stereo cameras. By rotating the rig about a vertical axis, we generate four multi-perspective panoramas by resampling the regular perspective images captured by the stereo cameras. Then a depth map is estimated from the four multi-perspective panoramas and an original perspective image using a multi-baseline matching technique with different types of epipolar constraints. The second one is composed of a single camera and two mirrors. By rotating the rig, we acquire a spatio-temporal volume that is made up of the sequential images captured by the camera. Then we estimate a depth map by extracting trajectories from the spatio-temporal volume by using a multi-baseline stereo technique by considering occlusions. We can consider both rotating rigs as a single rotating camera with a very large field of view (FOV), that offers a large baseline length in depth estimation. In addition, compared with a previous approach using two multi-perspective panoramas from a single rotating camera, our approach can reduce matching errors due to image noise, repeated patterns, and occlusions by multi-baseline stereo techniques. Experimental results using both synthetic and real images show that our approach produces high quality panoramic 3D reconstruction.

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14

Lee, Kang-San y Hyun-Soo Kang. "Calibration Method for Omnidirectional Stereo Camera with Large Baseline". Journal of the Korea Contents Association 10, n.º 6 (28 de junio de 2010): 10–17. http://dx.doi.org/10.5392/jkca.2010.10.6.010.

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15

She, Mengkun, Tim Weiß, Yifan Song, Peter Urban, Jens Greinert y Kevin Köser. "Marine bubble flow quantification using wide-baseline stereo photogrammetry". ISPRS Journal of Photogrammetry and Remote Sensing 190 (agosto de 2022): 322–41. http://dx.doi.org/10.1016/j.isprsjprs.2022.06.014.

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16

Chang, Yuan, Congyi Zhang, Yisong Chen y Guoping Wang. "Homography-guided stereo matching for wide-baseline image interpolation". Computational Visual Media 8, n.º 1 (27 de octubre de 2021): 119–33. http://dx.doi.org/10.1007/s41095-021-0225-9.

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AbstractImage interpolation has a wide range of applications such as frame rate-up conversion and free viewpoint TV. Despite significant progresses, it remains an open challenge especially for image pairs with large displacements. In this paper, we first propose a novel optimization algorithm for motion estimation, which combines the advantages of both global optimization and a local parametric transformation model. We perform optimization over dynamic label sets, which are modified after each iteration using the prior of piecewise consistency to avoid local minima. Then we apply it to an image interpolation framework including occlusion handling and intermediate image interpolation. We validate the performance of our algorithm experimentally, and show that our approach achieves state-of-the-art performance.

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17

Morgan, Gareth Llewellyn Keith, Jian Guo Liu y Hongshi Yan. "Precise Subpixel Disparity Measurement From Very Narrow Baseline Stereo". IEEE Transactions on Geoscience and Remote Sensing 48, n.º 9 (septiembre de 2010): 3424–33. http://dx.doi.org/10.1109/tgrs.2010.2046672.

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18

Sakamoto, Shizuo, Ingemar J. Cox y Johji Tajima. "A multiple-baseline stereo for precise human face acquisition". Pattern Recognition Letters 18, n.º 9 (septiembre de 1997): 923–31. http://dx.doi.org/10.1016/s0167-8655(97)00066-4.

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19

Rathnayaka, Pathum y Soon-Yong Park. "iGG-MBS: Iterative Guided-Gaussian Multi-Baseline Stereo Matching". IEEE Access 8 (2020): 99205–18. http://dx.doi.org/10.1109/access.2020.2997073.

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20

Matas, J., O. Chum, M. Urban y T. Pajdla. "Robust wide-baseline stereo from maximally stable extremal regions". Image and Vision Computing 22, n.º 10 (septiembre de 2004): 761–67. http://dx.doi.org/10.1016/j.imavis.2004.02.006.

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21

Mou, Xiaozheng y Han Wang. "Wide-Baseline Stereo-Based Obstacle Mapping for Unmanned Surface Vehicles". Sensors 18, n.º 4 (4 de abril de 2018): 1085. http://dx.doi.org/10.3390/s18041085.

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22

Feris, R., R. Raskar, Longbin Chen, Kar-Han Tan y M. Turk. "Multiflash Stereopsis: Depth-Edge-Preserving Stereo with Small Baseline Illumination". IEEE Transactions on Pattern Analysis and Machine Intelligence 30, n.º 1 (enero de 2008): 147–59. http://dx.doi.org/10.1109/tpami.2007.1136.

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23

Tola, E., V. Lepetit y P. Fua. "DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo". IEEE Transactions on Pattern Analysis and Machine Intelligence 32, n.º 5 (mayo de 2010): 815–30. http://dx.doi.org/10.1109/tpami.2009.77.

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24

Bian, Jilong, Jinfeng Li, Nana Wang y Liu Yang. "A Small Baseline Stereo Matching Method Based on Adaptive Weight". International Journal of Multimedia and Ubiquitous Engineering 10, n.º 9 (31 de octubre de 2015): 137–46. http://dx.doi.org/10.14257/ijmue.2015.10.9.15.

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25

Drouin, Marc-Antoine, Martin Trudeau y Sébastien Roy. "Improving Border Localization of Multi-Baseline Stereo Using Border-Cut". International Journal of Computer Vision 83, n.º 3 (3 de marzo de 2009): 233–47. http://dx.doi.org/10.1007/s11263-009-0223-3.

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26

Wang, Han, Wei Mou, Xiaozheng Mou, Shenghai Yuan, Soner Ulun, Shuai Yang y Bok-Suk Shin. "An Automatic Self-Calibration Approach for Wide Baseline Stereo Cameras Using Sea Surface Images". Unmanned Systems 03, n.º 04 (octubre de 2015): 277–90. http://dx.doi.org/10.1142/s230138501540004x.

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Stereo rig with wide baseline is necessary when accurate depth estimation for distant object is desired. However, in order to make calibration pattern to be viewed from both left and right cameras, the wider the baseline the bigger the calibration pattern is required. In contrast to the traditional stereo calibration method using calibration pattern, we propose a self-calibration approach that can estimate cameras' rotation matrices for stereo rig with wide baseline (3 m). Given images taken from left and right cameras, the relative roll and pitch angles between two cameras are recovered by aligning sea horizon in left and right images. The pitch angle is estimated by making the projections of one point at infinite distance appear at the same location in both images. A photometric minimization is applied to refine the rotation parameters. Compared with conventional checkerboard-based calibration techniques which require extra equipments or personnel, our approach only needs a pair of sea images. Moreover, unlike most self-calibration approaches, feature detection and matching are not required which makes it possible to apply our approach on featureless images. As a result, it is flexible and easy to implement our approach on sea surface images. Real world experiments demonstrate the feasibility of our approach.

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27

Yao, Guobiao, Alper Yilmaz, Fei Meng y Li Zhang. "Review of Wide-Baseline Stereo Image Matching Based on Deep Learning". Remote Sensing 13, n.º 16 (17 de agosto de 2021): 3247. http://dx.doi.org/10.3390/rs13163247.

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Strong geometric and radiometric distortions often exist in optical wide-baseline stereo images, and some local regions can include surface discontinuities and occlusions. Digital photogrammetry and computer vision researchers have focused on automatic matching for such images. Deep convolutional neural networks, which can express high-level features and their correlation, have received increasing attention for the task of wide-baseline image matching, and learning-based methods have the potential to surpass methods based on handcrafted features. Therefore, we focus on the dynamic study of wide-baseline image matching and review the main approaches of learning-based feature detection, description, and end-to-end image matching. Moreover, we summarize the current representative research using stepwise inspection and dissection. We present the results of comprehensive experiments on actual wide-baseline stereo images, which we use to contrast and discuss the advantages and disadvantages of several state-of-the-art deep-learning algorithms. Finally, we conclude with a description of the state-of-the-art methods and forecast developing trends with unresolved challenges, providing a guide for future work.

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28

Samson, Éric, Denis Laurendeau y Marc Parizeau. "Calibration of Stereo Pairs Using Speckle Metrology". Sensors 22, n.º 5 (24 de febrero de 2022): 1784. http://dx.doi.org/10.3390/s22051784.

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The accuracy of 3D reconstruction for metrology applications using active stereo pairs depends on the quality of the calibration of the system. Active stereo pairs are generally composed of cameras mounted on tilt/pan mechanisms separated by a constant or variable baseline. This paper presents a calibration approach based on speckle metrology that allows the separation of translation and rotation in the estimation of extrinsic parameters. To achieve speckle-based calibration, a device called an Almost Punctual Speckle Source (APSS) is introduced. Using the APSS, a thorough method for the calibration of extrinsic parameters of stereo pairs is described. Experimental results obtained with a stereo system called the Agile Stereo Pair (ASP) demonstrate that speckle-based calibration achieves better reconstruction performance than methods using standard calibration procedures. Although the experiments were performed with a specific stereo pair, such as the ASP, which is described in the paper, the speckle-based calibration approach using the APSS can be transposed to other stereo setups.

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29

Li, Jing, Zigang Li y Hong Zhao. "Efficient global stereo-matching method of general images under a long baseline based on baseline estimation". Applied Optics 60, n.º 27 (13 de septiembre de 2021): 8248. http://dx.doi.org/10.1364/ao.433231.

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30

Dou, Yiwen, Kuangrong Hao, Yongsheng Ding y Min Mao. "A Mean-Shift-Based Feature Descriptor for Wide Baseline Stereo Matching". Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/398756.

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We propose a novel Mean-Shift-based building approach in wide baseline. Initially, scale-invariance feature transform (SIFT) approach is used to extract relatively stable feature points. As to each matching SIFT feature point, it needs a reasonable neighborhood range so as to choose feature points set. Subsequently, in view of selecting repeatable and high robust feature points, Mean-Shift controls corresponding feature scale. At last, our approach is employed to depth image acquirement in wide baseline and Graph Cut algorithm optimizes disparity information. Compared with the existing methods such as SIFT, speeded up robust feature (SURF), and normalized cross-correlation (NCC), the presented approach has the advantages of higher robustness and accuracy rate. Experimental results on low resolution image and weak feature description in wide baseline confirm the validity of our approach.

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31

Watanabe, Takashi, Akira Kusano, Takayuki Fujiwara y Hiroyasu Koshimizu. "Quasi Multi-Baseline-Stereo Method with Single Camera for Reducing Occlusion". IEEJ Transactions on Electronics, Information and Systems 127, n.º 4 (2007): 652–58. http://dx.doi.org/10.1541/ieejeiss.127.652.

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32

Zhang, Dazhi, Yongtao Wang, Wenbing Tao y Chengyi Xiong. "Epipolar geometry estimation for wide baseline stereo by Clustering Pairing Consensus". Pattern Recognition Letters 36 (enero de 2014): 1–9. http://dx.doi.org/10.1016/j.patrec.2013.08.019.

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33

Watanabe, Takashi, Akira Kusano, Takayuki Fujiwara y Hiroyasu Koshimizu. "Quasi multi-baseline-stereo method with single camera for reducing occlusion". Electronics and Communications in Japan 93, n.º 1 (enero de 2010): 41–49. http://dx.doi.org/10.1002/ecj.10156.

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34

Yu, Zhi Jing y Sheng Fang Lu. "The Research on Modeling of Stereo Vision Measurement and System Accuracy in Non-Ideal Situation". Applied Mechanics and Materials 121-126 (octubre de 2011): 4837–41. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.4837.

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This paper presents the modeling of stereo vision measurement for solving the optimal spatial point under non-ideal circumstances, and then analyzes the error of stereo vision measurement system from the imaging feature location and camera internal parameters and external parameters, such as the focal length, the baseline distance, which plays a important role in optimization of system architecture and layout of measurement system.

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35

Yao, Guobiao, Alper Yilmaz, Li Zhang, Fei Meng, Haibin Ai y Fengxiang Jin. "Matching Large Baseline Oblique Stereo Images Using an End-to-End Convolutional Neural Network". Remote Sensing 13, n.º 2 (14 de enero de 2021): 274. http://dx.doi.org/10.3390/rs13020274.

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The available stereo matching algorithms produce large number of false positive matches or only produce a few true-positives across oblique stereo images with large baseline. This undesired result happens due to the complex perspective deformation and radiometric distortion across the images. To address this problem, we propose a novel affine invariant feature matching algorithm with subpixel accuracy based on an end-to-end convolutional neural network (CNN). In our method, we adopt and modify a Hessian affine network, which we refer to as IHesAffNet, to obtain affine invariant Hessian regions using deep learning framework. To improve the correlation between corresponding features, we introduce an empirical weighted loss function (EWLF) based on the negative samples using K nearest neighbors, and then generate deep learning-based descriptors with high discrimination that is realized with our multiple hard network structure (MTHardNets). Following this step, the conjugate features are produced by using the Euclidean distance ratio as the matching metric, and the accuracy of matches are optimized through the deep learning transform based least square matching (DLT-LSM). Finally, experiments on Large baseline oblique stereo images acquired by ground close-range and unmanned aerial vehicle (UAV) verify the effectiveness of the proposed approach, and comprehensive comparisons demonstrate that our matching algorithm outperforms the state-of-art methods in terms of accuracy, distribution and correct ratio. The main contributions of this article are: (i) our proposed MTHardNets can generate high quality descriptors; and (ii) the IHesAffNet can produce substantial affine invariant corresponding features with reliable transform parameters.

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36

Swenor, Bonnielin K., Jiangxia Wang, Varshini Varadaraj, Caterina Rosano, Kristine Yaffe, Marilyn Albert y Eleanor M. Simonsick. "Vision Impairment and Cognitive Outcomes in Older Adults: The Health ABC Study". Journals of Gerontology: Series A 74, n.º 9 (25 de octubre de 2018): 1454–60. http://dx.doi.org/10.1093/gerona/gly244.

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Abstract Background An association between visual impairment and cognitive outcomes has been documented, but there is limited research examining this relationship using multiple measures of vision. Methods Participants included non-demented individuals in Year 3 of the Visual impairment was assessed using visual acuity, contrast sensitivity, and stereo acuity. Cognitive function was defined using the digit symbol test and the Modified Mini-Mental State Examination (3MS). Incident cognitive impairment was defined as a 3MS score <80 or a decline >5 points following Year 3. Linear mixed effects models examined longitudinal associations adjusting for year, age, sex, race, education, smoking, depression, diabetes, study site, as well as interaction terms between the vision parameters and years in study, between baseline age and years in study, and quadratic terms of baseline age and years in study. Discrete Cox regression models examined the risk of incident cognitive impairment. Results Analyses included 2,444 participants (mean age = 74). Visual acuity, contrast sensitivity, and stereo acuity impairments were not associated with statistically significant changes in annual digit symbol test scores over 7 years of follow-up, as compared to those without these impairments. However, visual acuity, contrast sensitivity, and stereo acuity impairments were associated with greater declines in annual 3MS scores over 9 years. Participants with impaired visual acuity, contrast sensitivity, and stereo acuity had a greater risk of incident cognitive impairment. Conclusions Our results suggest that visual acuity, contrast sensitivity, and stereo acuity impairments may be risk factors for cognitive decline.

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37

Li, Ping y Yan Wen Wang. "Analysis on Structural Parameters of Binocular Stereo Vision System". Applied Mechanics and Materials 437 (octubre de 2013): 290–95. http://dx.doi.org/10.4028/www.scientific.net/amm.437.290.

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Through the analysis of present research and application situation of binocular stereo vision system, the paper indicates an opinion that the structural parameters of system are crucial to the measurement accuracy of system. This paper focuses on several parameters to discuss the effect on the measurement accuracy, such as the distance of baseline, angles between optical axis and baseline, projection angles and so on. According to measuring principle and mathematical model of binocular stereo vision system, through deriving formulas and drawing curves by means of MATLAB, the impact that different structural parameter has on measurement accuracy is analyzed. Finally, the correctness of theoretical analysis is proved by experiment and the research result is summarized.

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Masiero, A., F. Fissore, M. Piragnolo, A. Guarnieri, F. Pirotti y A. Vettore. "INITIAL EVALUATION OF 3D RECONSTRUCTION OF CLOSE OBJECTS WITH SMARTPHONE STEREO VISION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1 (26 de septiembre de 2018): 289–93. http://dx.doi.org/10.5194/isprs-archives-xlii-1-289-2018.

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<p><strong>Abstract.</strong> The Worldwide spread of relatively low cost mobile devices embedded with dual rear cameras enables the possibility of exploiting smartphone stereo vision for producing 3D models. Despite such idea is quite attractive, the small baseline between the two cameras restricts the depth discrimination ability of this kind of stereo vision systems. This paper presents the results obtained with a smartphone stereo vision system by using two rear cameras with different focal length: this operating condition clearly reduces the matchable area. Nevertheless, 3D reconstruction is still possible and the obtained results are evaluated for several camera-object distances.</p>

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Yu, Chanki y Sang Wook Lee. "Deep Photometric Stereo Network with Multi-Scale Feature Aggregation". Sensors 20, n.º 21 (3 de noviembre de 2020): 6261. http://dx.doi.org/10.3390/s20216261.

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We present photometric stereo algorithms robust to non-Lambertian reflection, which are based on a convolutional neural network in which surface normals of objects with complex geometry and surface reflectance are estimated from a given set of an arbitrary number of images. These images are taken from the same viewpoint under different directional illumination conditions. The proposed method focuses on surface normal estimation, where multi-scale feature aggregation is proposed to obtain a more accurate surface normal, and max pooling is adopted to obtain an intermediate order-agnostic representation in the photometric stereo scenario. The proposed multi-scale feature aggregation scheme using feature concatenation is easily incorporated into existing photometric stereo network architectures. Our experiments were performed with a DiLiGent photometric stereo benchmark dataset consisting of ten real objects, and they demonstrated that the accuracies of our calibrated and uncalibrated photometric stereo approaches were improved over those of baseline methods. In particular, our experiments also demonstrated that our uncalibrated photometric stereo outperformed the state-of-the-art method. Our work is the first to consider the multi-scale feature aggregation in photometric stereo, and we showed that our proposed multi-scale fusion scheme estimated the surface normal accurately and was beneficial to improving performance.

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40

Dong, Bo, Fancang Zeng y Bing Pan. "A Simple and Practical Single-Camera Stereo-Digital Image Correlation Using a Color Camera and X-Cube Prism". Sensors 19, n.º 21 (31 de octubre de 2019): 4726. http://dx.doi.org/10.3390/s19214726.

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A simple and practical full-frame single-camera stereo-digital image correlation (stereo-DIC) technique for three-dimensional (3D) shape, displacement, and deformation measurements is proposed. The technique uses a compact X-cube prism-based color separation device and a color camera to capture images of blue and red colors from different optical paths, and then extracts the surface 3D shape and deformation information of a test sample by processing the captured two sub-channel color images using regular stereo-DIC algorithm. Compared with the existing full-frame single-camera stereo-DICs, the proposed one eliminates the need for a beam splitter and two bandpass filters to capture images, and offers more simple, compact, and easy-to-use optical arrangement. This novel single-camera stereo-DIC technique was validated by a series of baseline experiments involving 3D surface reconstructions, translation tests, and full-field deformation measurements, which provide a new flexible and practical avenue for measuring surface 3D shape and deformation, particularly in microscopic and high-speed applications.

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41

Wang, Qiang, Haimeng Zhao, Zhenxin Zhang, Ximin Cui, Sana Ullah, Shanlin Sun y Fan Liu. "Line Matching Based on Viewpoint-Invariance for Stereo Wide-Baseline Aerial Images". Applied Sciences 8, n.º 6 (6 de junio de 2018): 938. http://dx.doi.org/10.3390/app8060938.

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42

Wang, Jie, Chenglei Peng, Ming Li, Yang Li y Sidan Du. "The study of stereo matching optimization based on multi-baseline trinocular model". Multimedia Tools and Applications 81, n.º 9 (22 de febrero de 2022): 12961–72. http://dx.doi.org/10.1007/s11042-022-12579-8.

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43

Heath, Garrett D. "Search and target acquisition: single line of sight versus wide baseline stereo". Optical Engineering 40, n.º 9 (1 de septiembre de 2001): 1914. http://dx.doi.org/10.1117/1.1390300.

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44

Lee, Onseok, Gunwoo Lee, Jangseok Oh, Mingi Kim y Chilhwan Oh. "An optimized in vivo multiple-baseline stereo imaging system for skin wrinkles". Optics Communications 283, n.º 23 (diciembre de 2010): 4840–45. http://dx.doi.org/10.1016/j.optcom.2010.07.005.

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45

Heinrich, K. y M. Mehltretter. "LEARNING MULTI-MODAL FEATURES FOR DENSE MATCHING-BASED CONFIDENCE ESTIMATION". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (28 de junio de 2021): 91–99. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-91-2021.

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Abstract. In recent years, the ability to assess the uncertainty of depth estimates in the context of dense stereo matching has received increased attention due to its potential to detect erroneous estimates. Especially, the introduction of deep learning approaches greatly improved general performance, with feature extraction from multiple modalities proving to be highly advantageous due to the unique and different characteristics of each modality. However, most work in the literature focuses on using only mono- or bi- or rarely tri-modal input, not considering the potential effectiveness of modalities, going beyond tri-modality. To further advance the idea of combining different types of features for confidence estimation, in this work, a CNN-based approach is proposed, exploiting uncertainty cues from up to four modalities. For this purpose, a state-of-the-art local-global approach is used as baseline and extended accordingly. Additionally, a novel disparity-based modality named warped difference is presented to support uncertainty estimation at common failure cases of dense stereo matching. The general validity and improved performance of the proposed approach is demonstrated and compared against the bi-modal baseline in an evaluation on three datasets using two common dense stereo matching techniques.

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46

George, Anand, Niko Koivumäki, Teemu Hakala, Juha Suomalainen y Eija Honkavaara. "Visual-Inertial Odometry Using High Flying Altitude Drone Datasets". Drones 7, n.º 1 (4 de enero de 2023): 36. http://dx.doi.org/10.3390/drones7010036.

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Positioning of unoccupied aerial systems (UAS, drones) is predominantly based on Global Navigation Satellite Systems (GNSS). Due to potential signal disruptions, redundant positioning systems are needed for reliable operation. The objective of this study was to implement and assess a redundant positioning system for high flying altitude drone operation based on visual-inertial odometry (VIO). A new sensor suite with stereo cameras and an inertial measurement unit (IMU) was developed, and a state-of-the-art VIO algorithm, VINS-Fusion, was used for localisation. Empirical testing of the system was carried out at flying altitudes of 40–100 m, which cover the common flight altitude range of outdoor drone operations. The performance of various implementations was studied, including stereo-visual-odometry (stereo-VO), monocular-visual-inertial-odometry (mono-VIO) and stereo-visual-inertial-odometry (stereo-VIO). The stereo-VIO provided the best results; the flight altitude of 40–60 m was the most optimal for the stereo baseline of 30 cm. The best positioning accuracy was 2.186 m for a 800 m-long trajectory. The performance of the stereo-VO degraded with the increasing flight altitude due to the degrading base-to-height ratio. The mono-VIO provided acceptable results, although it did not reach the performance level of the stereo-VIO. This work presented new hardware and research results on localisation algorithms for high flying altitude drones that are of great importance since the use of autonomous drones and beyond visual line-of-sight flying are increasing and will require redundant positioning solutions that compensate for potential disruptions in GNSS positioning. The data collected in this study are published for analysis and further studies.

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47

De Gregorio, Daniele, Matteo Poggi, Pierluigi Zama Ramirez, Gianluca Palli, Stefano Mattoccia y Luigi Di Stefano. "Beyond the Baseline: 3D Reconstruction of Tiny Objects With Single Camera Stereo Robot". IEEE Access 9 (2021): 119755–65. http://dx.doi.org/10.1109/access.2021.3108626.

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48

Li, Hongdong y Richard Hartley. "Inverse tensor transfer with applications to novel view synthesis and multi-baseline stereo". Signal Processing: Image Communication 21, n.º 9 (octubre de 2006): 724–38. http://dx.doi.org/10.1016/j.image.2006.07.004.

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49

Katai-Urban, G., V. Otte, N. Kees, Z. Megyesi y P. S. Bixel. "STEREO RECONSTRUCTION OF ATMOSPHERIC CLOUD SURFACES FROM FISH-EYE CAMERA IMAGES". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (9 de junio de 2016): 49–56. http://dx.doi.org/10.5194/isprs-archives-xli-b3-49-2016.

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In this article a method for reconstructing atmospheric cloud surfaces using a stereo camera system is presented. The proposed camera system utilizes fish-eye lenses in a flexible wide baseline camera setup. The entire workflow from the camera calibration to the creation of the 3D point set is discussed, but the focus is mainly on cloud segmentation and on the image processing steps of stereo reconstruction. Speed requirements, geometric limitations, and possible extensions of the presented method are also covered. After evaluating the proposed method on artificial cloud images, this paper concludes with results and discussion of possible applications for such systems.

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50

Katai-Urban, G., V. Otte, N. Kees, Z. Megyesi y P. S. Bixel. "STEREO RECONSTRUCTION OF ATMOSPHERIC CLOUD SURFACES FROM FISH-EYE CAMERA IMAGES". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (9 de junio de 2016): 49–56. http://dx.doi.org/10.5194/isprsarchives-xli-b3-49-2016.

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In this article a method for reconstructing atmospheric cloud surfaces using a stereo camera system is presented. The proposed camera system utilizes fish-eye lenses in a flexible wide baseline camera setup. The entire workflow from the camera calibration to the creation of the 3D point set is discussed, but the focus is mainly on cloud segmentation and on the image processing steps of stereo reconstruction. Speed requirements, geometric limitations, and possible extensions of the presented method are also covered. After evaluating the proposed method on artificial cloud images, this paper concludes with results and discussion of possible applications for such systems.

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