Обработка перекрытий в задачах отслеживания объектов в видеопотоке
Опубликовано: 20.11.2013
Авторы: Тассов К.Л., Бекасов Д.Е.
Опубликовано в выпуске: #6(18)/2013
DOI: 10.18698/2308-6033-2013-6-1099
Раздел: Информационные технологии
Представлено описание задачи отслеживания объектов в видеопотоке, введены основные понятия проблемной области, освещены типовые решения задачи. Более подробно рассмотрены несколько решений с позиции проблемы перекрытий как одной из наиболее весомых. Приведены основные направления будущих исследований.
Литература
[1] Maggio E., Cavallaro A. Video tracking theory and practice. Wiley, 2011
[2] HSL // Wikipedia. URL. http://ru.wikipedia.org/wiki/HSL
[3] Moravec H. Towards automatic visual obstacle avoidance. Proceedings of the 5th International Joint Conference on Artificial Intelligence. Cambridge, MA, 1977
[4] Harris C., Stephens M. A combined corner and edge detector. Proceedings of the 4th Alvey Vision Conference, 1988, pp. 147-151
[5] Meier T., Ngan K.N. Automatic segmentation of moving objects for video object plane generation. IEEE Transactions on Circuits and Systems for Video Technology, 1998, pp. 525-538
[6] Alatan A.A., Onural L., Wollborn M., Mech R., Tuncel E., Sikora T. Image sequence analysis for emerging interactive multimedia services-the European COST 211 framework. IEEE Transactions on Circuits and Systems for Video Technology, 1998, pp. 802-813
[7] Bezdek J.C., Ehrlich R., Full W. Fcm: The fuzzy c-means clustering algorithm. Computers Geosciences, 1984, pp. 191-203
[8] Cavallaro T. Ebrahimi. Interaction between high-level and low-level image analysis for semantic video object extraction. EURASIP Journal on Applied Signal Processing, 2004, no. 6, pp. 786-797
[9] Stauffer C., Grimson W.E.L. Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, pp. 747-757
[10] Nevatia Wu R. Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors. In Proceedings of International Conference on Computer Vision. Washington, IEEE Computer Society, 2005, pp. 90-97
[11] Sundararajan K. Unified point-edgelet feature tracking. A Thesis Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Master of Science Electrical Engineering, 2011
[12] Bar-Shalom Y., Fortmann T. Tracking and Data Association. New York, Academic Press, 1988
[13] Comaniciu D., Ramesh V., Meer P. Kernel-based object tracking. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2003, pp. 564-577
[14] Koller D., Danilidis K., Nagel H. Model-based object tracking in monocular image sequences of road traffic scenes. International Journal of Computer Vision, 1993, pp. 257-281
[15] Sundaresan A., Chellappa R.. Multi-camera tracking of articulated human motion using shape and motion cues. IEEE Transactions on Image Processing, 2009, pp. 2114-2126
[16] Beymer D., McLauchlan P., Coifman B., Malik J. A real-time computer vision system for measuring traffic parameters. Proceedings of Computer Vision and Pattern Recognition (CVPR), San Juan, Puerto Rico, 1997, pp. 495-501
[17] Isard M., Blake A. Condensation — conditional density propagation for visual tracking. International Journal of Computer Vision, 1998, pp. 5-28
[18] Xiao J., Baker S., Matthews I. and Kanade T. Image on 3D AAM from realtime combined 2D+3D active appearance models. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Washington, DC, 2004, pp. 535-542
[19] Shi J., Tomasi C. Good features to track. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Seattle, USA, 1994, pp. 593-600
[20] Freeman W.T., Roth M. Orientation histograms for hand gesture recognition. Proceedings of the Workshop on Automatic Face and Gesture Recognition. Zurich, Switzerland, 1995, pp. 296-301
[21] Lowe D.G. Object recognition from local scale-invariant features. Proceedings of the International Conference on Computer Vision. Corfu, Greece, 1999, pp. 1150-1157
[22] Zhou S., Chellappa R., Moghaddam B. Visual tracking and recognition using appearance-based modeling in particle filters. IEEE Transactions on Image Processing, 2004, pp. 491-1506
[23] Maggio E., Cavallaro A. Hybrid particle filter and mean shift tracker with adaptive transition model. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2. Philadelphia, PA, 2005, pp. 221-224
[24] Kalal Z., Mikolajczyk K., Matas J. Tracking-Learning-Detection. IEEE transactions on pattern analysis and machine intelligence, 2010, vol. 6, no. 1, pp. 114
[25] Rahimi L., P. Morency, T. Darrell. Reducing drift in differential tracking. Computer Vision and Image Understanding, 2008, vol. 109, no. 2, pp. 97-111
[26] Jepson D., Fleet D.J., El-Maraghi T.F. Robust Online Appearance Models for Visual Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, pp. 1296-1311
[27] Black M.J., Jepson A.D. Eigentracking: Robust matching and tracking of articulated objects using a view-based representation. International Journal of Computer Vision, 1998, vol. 26, no. 1, pp. 63-84
[28] Kwon J., Lee K.M. Visual Tracking Decomposition. Conference on Computer Vision and Pattern Recognition, 2010
[29] Yang M., Wu Y., Hua G. Context-aware visual tracking. IEEE transactions on pattern analysis and machine intelligence, 2006, vol. 31, pp. 1195-209
[30] Babenko B., Yang M.-H., Belongie S. Visual Tracking with Online Multiple Instance Learning. Conference on Computer Vision and Pattern Recognition, 2009
[31] Lowe G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004, vol. 60, no. 2, pp. 91-110
[32] Viola P., Jones M. Rapid object detection using a boosted cascade of simple features. Conference on Computer Vision and Pattern Recognition, 2001
[33] Вражнов Д.А., Шаповалов А.В., Николаев В.В. О качестве работы алгоритмов слежения за объектами на видео. Компьютерные исследования и моделирование, 2012, т. 4, № 2, с. 303-313
[34] Апальков И.В., Хрящев В.В. Удаление шума из изображений на основе нелинейных алгоритмов с использованием ранговой статистики. Ярославский государственный университет имени П.Г. Демидова, 2007
[35] Pan J., Hu B. Robust Occlusion Handling in Object Tracking. IEEE Computer Vision and Pattern Recognition, 2007, pp. 1-8
[36] Nguyen H.T., Smeulders A.W.M. Fast occluded object tracking by a robust appearance filter. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2004, pp. 1099-1104
[37] Hariharakrishnan K., Schonfeld D. Fast object tracking using adaptive block matching. IEEE Trans. on Multimedia, 2005, pp. 853-859
[38] L. Elgammal, Davis S. Probabilistic framework for segmenting people under occlusion. Proc. Of IEEE 8th International Conference on Computer Vision, 2001
[39] Senior A.W., Hampapur A., Brown L.M., Tian Y., Pankanti S., Bolle R. M. Appearance Models for Occlusion Handling. 2nd International Workshop on Performance Evaluation of Tracking and Surveillance systems, 2001
[40] Wu Y., Yu T., Hua G. Tracking Appearances with Occlusions. IEEE Computer Vision and Pattern Recognition, 2003