AIRR  >> Vol. 4 No. 3 (August 2015)


徐佳龙:海军驻南京地区航空军事代表室,江苏 南京

目标跟踪轨迹校正目标检测Object Tracking Track Alignment Object Detection



Object tracking is a process to locate an interested object in a series of image, so as to reconstruct the moving object’s track. This paper presents a summary of related works and analyzes the characteristics of the algorithm. At last, some future directions are suggested.

徐佳龙. 目标跟踪相关研究综述[J]. 人工智能与机器人研究, 2015, 4(3): 17-22.


[1] Yilmaz, A., Javed, O. and Shah, M. (2006) Object tracking: A survey. ACM Computing Surveys, 38, 1-45.
[2] 陈宁强 (2010) 多目标跟踪方法研究综述. 科技信息, 21-26.
[3] 尹宏鹏 (2009) 基于计算机视觉的运动目标跟踪算法研究. 重庆大学博士论文, 重庆.
[4] Harris, C.G. and Stephens, M. (1988) A combined corner and edge detector. Proceedings of 4th Alvey Vision Conference, 189-192.
[5] Lowe, D. (2004) Distinctive image features from scale-invariant key points. International Journal Computer Vision, 60, 91-110.
[6] Mikolajczyk, K. and Schmid, C. (2002) An affine invariant interest point detector. European Conference on Computer Vision, 128-142.
[7] Lochner, M. and Trick, L. (2014) Multiple-object tracking while driving: The multiple-vehicle tracking task. Attention, Perception, & Psychophysics, 76, 2326-2345.
[8] Meyerhoff, H., Papenmeier, F. and Huff, M. (2013) Object-based integration of motion information during attentive tracking. Perception, 42, 119-121.
[9] Chevalier, F., Dragicevic, P. and Franconeri, S. (2014) The not-so-staggering effect of staggered animated transitions on visual tracking. IEEE Transactions on Visualization and Computer Graphics, 20, 2241-2250.
[10] Stauffer, C. and Grimson, W. (2000) Learning patterns of activity using real time tracking. IEEE Transaction Pattern Analysis and Machine Intelligence, 22, 747-767.
[11] Oliver, N., Rosario, B. and Pentland, A. (2000) A Bayesian computer vision system for modeling human interactions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 831-843.
[12] Feria, C. (2013) Speed has an effect on multiple-object tracking independently of the number of close encounters between targets and distractors. Attention, Perception, & Psychophysics, 75, 53-67.
[13] Monnet, A., Mittal, A., Paragios, N. and Ramesh, V. (2003) Background modeling and subtraction of dynamic scenes. Proceedings of the Ninth IEEE International Conference on Computer Vision, Nice, 13-16 October 2003, 1305-1312.
[14] Lukavsky, J. (2013) Eye movements in repeated multiple object tracking. Journal of Vision, 13, 9-16.
[15] Rowley, H., Baluja, S. and Kanade, T. (2014) Tracking by location and features: Object correspondence across spatiotemporal discontinuities during multiple object tracking. Journal of Experimental Psychology: Human Perception and Performance, 40, 159-171.
[16] Viola, P., Jones, M. and Snow, D. (2003) Detecting pedestrians using patterns of motion and appearance. Proceedings of the Ninth IEEE International Conference on Computer Vision, Nice, 13-16 October 2003, 734-741.
[17] Black, M. and Jepson, A. (1998) Eigen-tracking: Robust matching and tracking of articulated objects using a view- based representation. International Journal of Computation Vision, 26, 63-84.
[18] Avidan, S. (2001) Support vector tracking. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Kauai, 8-14 December 2001, 184-191.
[19] Rehman, A., Kihara, K., Matsumoto, A. and Ohtsuka, S. (2015) Attentive tracking of moving objects in real 3D space. Vision Research, 109, 1-10.
[20] Franconeri, S., Jonathan, S. and Scimeca, J. (2010) Tracking multiple objects is limited only by object spacing, not speed, time, or capacity. Psychological Science, 21, 920-925.
[21] Zhang, S.L., Huang, Q.M., Jiang, S.Q., Gao, W. and Tian, Q. (2010) Affective visualization and retrieval for music video. IEEE Transactions on Multimedia, 12, 510-522.