Object detection and tracking methods: A comprehensive review
Yıl 2017,
Cilt: 6 Sayı: 2, 40 - 49, 16.12.2017
Kazım Hanbay
,
Hüseyin Üzen
Kaynakça
- [1] Hjelmås E., Kee L.B., Face Detection: A Survey,Computer vision and image understanding, 83, 236–274., 2001
- [2] Anagnostopoulos C.-N.E., Anagnostopoulos I.E., Psoroulas I.D., Loumos, V., Kayafas, E., License Plate Recognition From Still Images and Video Sequences: A Survey,IEEE Transactions on intelligent transportation systems, 9, 3:377–391, 2008
- [3] Balaji S.R., KarthikeyanS.,A survey on moving object tracking using image processing, 2017 11th International Conference on Intelligent Systems and Control (ISCO), IEEE, pp. 469–474, 2017
- [4] Wang D., Unsupervised video segmentation based on watersheds and temporal tracking,IEEE Transactions on Circuits and Systems for video Technology, 8.5:539–546, 1998
- [5] Chen Y., Yang X., Zhong B., Pan S., et al., CNNTracker: Online discriminative object tracking via deep convolutional neural network,Applied Soft Computing, 38:1088–1098, 2016
- [6] Luo W., Xing J., Milan A., Zhang X., Multiple Object Tracking: A Literature Review,arXiv Prepr. arXiv1409.7618, 2014
- [7] Risha K.P., Kumar A.C., Novel Method of Detecting Moving Object in Video,Procedia Technology, 24:1055–1060, 2016
- [8] Avidan S., Support vector tracking,IEEE transactions on pattern analysis and machine intelligence, 26.8: 1064-1072, 2004
- [9] Hinton G., Deng L., Yu D., Dahl G., Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups,IEEE Signal Processing Magazine, 29.6: 82-97, 2012
- [10] Krizhevsky A., Sutskever I., Hinton G.E., ImageNet Classification with Deep Convolutional Neural Networks, In: Advances in neural information processing systems, p. 1097-1105,2012
- [11] Szegedy C., Liu W., Jia Y., Sermanet P., Going Deeper With Convolutions, In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1–9, 2015
- [12] Taigman, Y., Yang, M., Ranzato, M., Wolf, L., DeepFace: Closing the gap to human-level performance in face verification, In: Proceedings of the IEEE conference on computer vision and pattern recognition, p. 1701-1708, 2014
- [13] Wu Y., Lim J., Yang M.-H., Online Object Tracking: A Benchmark, In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2411-2418, 2013
- [14] Karasulu B., Videolardaki Hareketli Nesnelerin Tespit Ve Takibi İçin Uyarlanabilir Arkaplan Çıkarımı Yaklaşımı Tabanlı Bir Sistem,Uludağ Üniversitesi Mühendislik-Mimarlık Fakültesi Dergis, 18, 2013
- [15] Shaikh S.H., Saeed K., Chaki N.,Moving Object Detection Approaches, Challenges and Object Tracking, In: Moving Object Detection Using Background Subtraction. Springer International Publishing, p. 5-14, 2014
- [16] Aldhaheri A.R., Edirisinghe E.A., Detection and Classification of a Moving Object in a Video Stream, In: Proc. of the Intl. Conf. on Advances in Computing and Information Technology-ACIT, 2014.
- [17] Hardas A., Vibha M., Moving Object Detection using Background Subtraction Shadow Removal and Post Processing,Int. J. Comput. Appl., 975–8887, 2015
- [18] Li G., Wang Y., Shu W., Real-Time Moving Object Detection for Video Monitoring Systems, In: Intelligent Information Technology Application, 2008. IITA'08. Second International Symposium on, IEEE, pp. 163–166, 2008
- [19] Martin C., Background Subtraction Using Running Gaussian Average: a Color Channel Comparison,In: Seminar aus Bildverarbeitung und Mustererkennung, 2014
- [20] Manipriya S., Mala C., Mathew S., Performance Analysis of Spatial Color Information for Object Detection Using Background Subtraction,IERI Procedia, 10:63–69, 2014
- [21] Stauffer, C., GrimsonW.E.L.,Adaptive background mixture models for real-time tracking, Proceedings,1999. IEEE Computer Society Conference on, IEEE, pp. 246–252, 1999
- [22] Doyle D.D., Jennings A.L., Black J.T., Optical flow background estimation for real-time pan/tilt camera object tracking,Measurement, 48:195–207, 2014
- [23] Tiwari, M., Singhai, R., A Review of Detection and Tracking of Object from Image and Video Sequences,International Journal of Computational Intelligence Research, 13, 973–1873, 2017
- [24] Chate M., Amudha S., Gohokar V., Object Detection and tracking in Video Sequences,ACEEE International Journal on signal & Image processing, 3, 2012,
- [25] Mohan A.S., Resmi R., Video image processing for moving object detection and segmentation using background subtraction, In: Computational Systems and Communications (ICCSC), 2014 First International Conference on,IEEE, pp. 288–292, 2014
- [26] Haritaoglu I., Harwood D., Davis L.S., W/sup 4/: real-time surveillance of people and their activities,IEEE Transactions on pattern analysis and machine intelligence, 22, 809–830, 2000
- [27] Zhiqiang W., Xiaopeng J., Peng W., Real-time moving object detection for video monitoring systems,Journal of Systems Engineering and Electronics,17, 731–736, 2006
- [28] Zhang T., Liu Z., Lian X., Wang X., Study on moving-objects detection technique in video surveillance system, Chinese Control and Decision Conference, IEEE, pp. 2375–2380, 2010
- [29] Krishna M.T.G., Ravishankar M., Babu D.R.R., Automatic detection and tracking of moving objects in complex environments for video surveillance applications, In: Electronics Computer Technology (ICECT), 2011 3rd International Conference on,IEEE, pp. 234–238, 2011
- [30] Due Trier., Jain A.K., Taxt T., Feature extraction methods for character recognition-A survey, PatternRecognition, 29, 641–662, 1996.
- [31] Fan L., Wang Z., Cail B., Tao C., A survey on multiple object tracking algorithm, In: Information and Automation (ICIA), 2016 IEEE International Conference on, IEEE, pp. 1855–1862, 2016
- [32] Javed O., Shah M., Tracking and object classification for automated surveillance, In: European Conference on Computer Vision. Springer, Berlin, Heidelberg, pp. 343-357, 2002
- [33] Hu, W., Tan, T., Wang, L., Maybank, S., A Survey on Visual Surveillance of Object Motion and Behaviors, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 34.3: 334-352, 2004
- [34] Talu M.F., Nesne Takip Yöntemlerinin Sınıflandırılması,İstanbul Ticaret Üniversitesi Fen Bilim. Derg., 18, 45–63, 2010
- [35] Yilmaz A., Javed O., Shah M., Object Tracking: A Survey,ACM computing surveys., 38, 2006
- [36] Parekh H.S., Thakore D.G., Jaliya U.K., A survey on object detection and tracking methods, International Journal of Innovative Research in Computer and Communication Engineering, 2.2: 2970-2979. 2014
- [37] Bagherpour P., Cheraghi S.A., Mokji M.B.M., Upper Body Tracking Using KLT and Kalman Filter, Procedia Computer Science, 13, 185–191, 2012
- [38] Wang, N., Yeung, D.-Y., Learning a deep compact image representation for visual tracking, Advances in neural information processing systems., p. 809-817, 2013.
- [39] Zhou X, Xie L, Zhang P, Zhang Y. An ensemble of deep neural networks for object tracking, In: Image Processing (ICIP), 2014 IEEE International Conference on, IEEE, p. 843-847, 2014
- [40] Zhang D., Maei H., Wang X., Wang Y.-F., Deep Reinforcement Learning for Visual Object Tracking in Videos,arXiv Prepr. arXiv1701.08936, 2017
- [41] Girshick R., Donahue J., Darrell T., Malik J., Rich feature hierarchies for accurate object detection and semantic segmentation, In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.580–587, 2014
- [42] Behrendt K., Novak L., Botros R., A deep learning approach to traffic lights: Detection, tracking, and classification, In: Robotics and Automation (ICRA), 2017 IEEE International Conference on, pp. 1370–1377, 2017
- [43] Gordon D., Farhadi A., Fox D., Re3: Real-Time Recurrent Regression Networks for Object Tracking, arXiv preprint arXiv:1705.06368, 2017.
- [44] Bae S.-H., Yoon K.-J., Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
Nesne tespit ve takip metotları: Kapsamlı bir derleme
Yıl 2017,
Cilt: 6 Sayı: 2, 40 - 49, 16.12.2017
Kazım Hanbay
,
Hüseyin Üzen
Kaynakça
- [1] Hjelmås E., Kee L.B., Face Detection: A Survey,Computer vision and image understanding, 83, 236–274., 2001
- [2] Anagnostopoulos C.-N.E., Anagnostopoulos I.E., Psoroulas I.D., Loumos, V., Kayafas, E., License Plate Recognition From Still Images and Video Sequences: A Survey,IEEE Transactions on intelligent transportation systems, 9, 3:377–391, 2008
- [3] Balaji S.R., KarthikeyanS.,A survey on moving object tracking using image processing, 2017 11th International Conference on Intelligent Systems and Control (ISCO), IEEE, pp. 469–474, 2017
- [4] Wang D., Unsupervised video segmentation based on watersheds and temporal tracking,IEEE Transactions on Circuits and Systems for video Technology, 8.5:539–546, 1998
- [5] Chen Y., Yang X., Zhong B., Pan S., et al., CNNTracker: Online discriminative object tracking via deep convolutional neural network,Applied Soft Computing, 38:1088–1098, 2016
- [6] Luo W., Xing J., Milan A., Zhang X., Multiple Object Tracking: A Literature Review,arXiv Prepr. arXiv1409.7618, 2014
- [7] Risha K.P., Kumar A.C., Novel Method of Detecting Moving Object in Video,Procedia Technology, 24:1055–1060, 2016
- [8] Avidan S., Support vector tracking,IEEE transactions on pattern analysis and machine intelligence, 26.8: 1064-1072, 2004
- [9] Hinton G., Deng L., Yu D., Dahl G., Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups,IEEE Signal Processing Magazine, 29.6: 82-97, 2012
- [10] Krizhevsky A., Sutskever I., Hinton G.E., ImageNet Classification with Deep Convolutional Neural Networks, In: Advances in neural information processing systems, p. 1097-1105,2012
- [11] Szegedy C., Liu W., Jia Y., Sermanet P., Going Deeper With Convolutions, In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1–9, 2015
- [12] Taigman, Y., Yang, M., Ranzato, M., Wolf, L., DeepFace: Closing the gap to human-level performance in face verification, In: Proceedings of the IEEE conference on computer vision and pattern recognition, p. 1701-1708, 2014
- [13] Wu Y., Lim J., Yang M.-H., Online Object Tracking: A Benchmark, In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2411-2418, 2013
- [14] Karasulu B., Videolardaki Hareketli Nesnelerin Tespit Ve Takibi İçin Uyarlanabilir Arkaplan Çıkarımı Yaklaşımı Tabanlı Bir Sistem,Uludağ Üniversitesi Mühendislik-Mimarlık Fakültesi Dergis, 18, 2013
- [15] Shaikh S.H., Saeed K., Chaki N.,Moving Object Detection Approaches, Challenges and Object Tracking, In: Moving Object Detection Using Background Subtraction. Springer International Publishing, p. 5-14, 2014
- [16] Aldhaheri A.R., Edirisinghe E.A., Detection and Classification of a Moving Object in a Video Stream, In: Proc. of the Intl. Conf. on Advances in Computing and Information Technology-ACIT, 2014.
- [17] Hardas A., Vibha M., Moving Object Detection using Background Subtraction Shadow Removal and Post Processing,Int. J. Comput. Appl., 975–8887, 2015
- [18] Li G., Wang Y., Shu W., Real-Time Moving Object Detection for Video Monitoring Systems, In: Intelligent Information Technology Application, 2008. IITA'08. Second International Symposium on, IEEE, pp. 163–166, 2008
- [19] Martin C., Background Subtraction Using Running Gaussian Average: a Color Channel Comparison,In: Seminar aus Bildverarbeitung und Mustererkennung, 2014
- [20] Manipriya S., Mala C., Mathew S., Performance Analysis of Spatial Color Information for Object Detection Using Background Subtraction,IERI Procedia, 10:63–69, 2014
- [21] Stauffer, C., GrimsonW.E.L.,Adaptive background mixture models for real-time tracking, Proceedings,1999. IEEE Computer Society Conference on, IEEE, pp. 246–252, 1999
- [22] Doyle D.D., Jennings A.L., Black J.T., Optical flow background estimation for real-time pan/tilt camera object tracking,Measurement, 48:195–207, 2014
- [23] Tiwari, M., Singhai, R., A Review of Detection and Tracking of Object from Image and Video Sequences,International Journal of Computational Intelligence Research, 13, 973–1873, 2017
- [24] Chate M., Amudha S., Gohokar V., Object Detection and tracking in Video Sequences,ACEEE International Journal on signal & Image processing, 3, 2012,
- [25] Mohan A.S., Resmi R., Video image processing for moving object detection and segmentation using background subtraction, In: Computational Systems and Communications (ICCSC), 2014 First International Conference on,IEEE, pp. 288–292, 2014
- [26] Haritaoglu I., Harwood D., Davis L.S., W/sup 4/: real-time surveillance of people and their activities,IEEE Transactions on pattern analysis and machine intelligence, 22, 809–830, 2000
- [27] Zhiqiang W., Xiaopeng J., Peng W., Real-time moving object detection for video monitoring systems,Journal of Systems Engineering and Electronics,17, 731–736, 2006
- [28] Zhang T., Liu Z., Lian X., Wang X., Study on moving-objects detection technique in video surveillance system, Chinese Control and Decision Conference, IEEE, pp. 2375–2380, 2010
- [29] Krishna M.T.G., Ravishankar M., Babu D.R.R., Automatic detection and tracking of moving objects in complex environments for video surveillance applications, In: Electronics Computer Technology (ICECT), 2011 3rd International Conference on,IEEE, pp. 234–238, 2011
- [30] Due Trier., Jain A.K., Taxt T., Feature extraction methods for character recognition-A survey, PatternRecognition, 29, 641–662, 1996.
- [31] Fan L., Wang Z., Cail B., Tao C., A survey on multiple object tracking algorithm, In: Information and Automation (ICIA), 2016 IEEE International Conference on, IEEE, pp. 1855–1862, 2016
- [32] Javed O., Shah M., Tracking and object classification for automated surveillance, In: European Conference on Computer Vision. Springer, Berlin, Heidelberg, pp. 343-357, 2002
- [33] Hu, W., Tan, T., Wang, L., Maybank, S., A Survey on Visual Surveillance of Object Motion and Behaviors, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 34.3: 334-352, 2004
- [34] Talu M.F., Nesne Takip Yöntemlerinin Sınıflandırılması,İstanbul Ticaret Üniversitesi Fen Bilim. Derg., 18, 45–63, 2010
- [35] Yilmaz A., Javed O., Shah M., Object Tracking: A Survey,ACM computing surveys., 38, 2006
- [36] Parekh H.S., Thakore D.G., Jaliya U.K., A survey on object detection and tracking methods, International Journal of Innovative Research in Computer and Communication Engineering, 2.2: 2970-2979. 2014
- [37] Bagherpour P., Cheraghi S.A., Mokji M.B.M., Upper Body Tracking Using KLT and Kalman Filter, Procedia Computer Science, 13, 185–191, 2012
- [38] Wang, N., Yeung, D.-Y., Learning a deep compact image representation for visual tracking, Advances in neural information processing systems., p. 809-817, 2013.
- [39] Zhou X, Xie L, Zhang P, Zhang Y. An ensemble of deep neural networks for object tracking, In: Image Processing (ICIP), 2014 IEEE International Conference on, IEEE, p. 843-847, 2014
- [40] Zhang D., Maei H., Wang X., Wang Y.-F., Deep Reinforcement Learning for Visual Object Tracking in Videos,arXiv Prepr. arXiv1701.08936, 2017
- [41] Girshick R., Donahue J., Darrell T., Malik J., Rich feature hierarchies for accurate object detection and semantic segmentation, In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.580–587, 2014
- [42] Behrendt K., Novak L., Botros R., A deep learning approach to traffic lights: Detection, tracking, and classification, In: Robotics and Automation (ICRA), 2017 IEEE International Conference on, pp. 1370–1377, 2017
- [43] Gordon D., Farhadi A., Fox D., Re3: Real-Time Recurrent Regression Networks for Object Tracking, arXiv preprint arXiv:1705.06368, 2017.
- [44] Bae S.-H., Yoon K.-J., Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017