An Efficient Multiple Object Detection and Tracking Framework for Automatic Counting and Video Surveillance Applications

被引:52
作者
del-Blanco, Carlos R. [1 ]
Jaureguizar, Fernando [1 ]
Garcia, Narciso [1 ]
机构
[1] Univ Politecn Madrid, ETSI Telecomunicac, Grp Tratamiento Imagenes, E-28040 Madrid, Spain
关键词
Moving object detection; multiple object tracking; object counting; video surveillance applications; particle filtering; IP cameras; real-time applications; SPLIT;
D O I
10.1109/TCE.2012.6311328
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Automatic visual object counting and video surveillance have important applications for home and business environments, such as security and management of access points. However, in order to obtain a satisfactory performance these technologies need professional and expensive hardware, complex installations and setups, and the supervision of qualified workers. In this paper, an efficient visual detection and tracking framework is proposed for the tasks of object counting and surveillance, which meets the requirements of the consumer electronics: off-the-shelf equipment, easy installation and configuration, and unsupervised working conditions. This is accomplished by a novel Bayesian tracking model that can manage multimodal distributions without explicitly computing the association between tracked objects and detections. In addition, it is robust to erroneous, distorted and missing detections. The proposed algorithm is compared with a recent work, also focused on consumer electronics, proving its superior performance(1).
引用
收藏
页码:857 / 862
页数:6
相关论文
共 14 条
[1]   A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking [J].
Arulampalam, MS ;
Maskell, S ;
Gordon, N ;
Clapp, T .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2002, 50 (02) :174-188
[2]   Fitting Multiple Connected Ellipses to an Image Silhouette Hierarchically [J].
Da Xu, Richard Yi ;
Kemp, Michael .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (07) :1673-1682
[3]   VISUAL TRACKING OF MULTIPLE INTERACTING OBJECTS THROUGH RAO-BLACKWELLIZED DATA ASSOCIATION PARTICLE FILTERING [J].
del Blanco, Carlos R. ;
Jaureguizar, Fernando ;
Garcia, Narciso .
2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, :821-824
[4]  
Del-Blanco CR, 2011, IEEE IMAGE PROC, P1437, DOI 10.1109/ICIP.2011.6115712
[5]   On sequential Monte Carlo sampling methods for Bayesian filtering [J].
Doucet, A ;
Godsill, S ;
Andrieu, C .
STATISTICS AND COMPUTING, 2000, 10 (03) :197-208
[6]   Split and merge data association filter for dense multi-target tracking [J].
Genovesio, A ;
Olivo-Marin, JC .
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 4, 2004, :677-680
[7]  
Khan Z, 2005, PROC CVPR IEEE, P605
[8]   Fast and Robust Algorithm of Tracking Multiple Moving Objects for Intelligent Video Surveillance Systems [J].
Kim, Jong Sun ;
Yeom, Dong Hae ;
Joo, Young Hoon .
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2011, 57 (03) :1165-1170
[9]   Target tracking with incomplete detection [J].
Ma, Yunqian ;
Yu, Qian ;
Cohen, Isaac .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2009, 113 (04) :580-587
[10]   Background subtraction techniques: a review [J].
Piccardi, M .
2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7, 2004, :3099-3104