MMM-TJU at TRECVID 2010

Surveillance Event Detection Semantic event detection in the huge amount of surveillance video in both retrospective and real-time styles is essential to a variety of higher-level applications in the public security. In TRECVID 2010, to overcome the limitations of the traditional human action analysis method with human detection/tracking and domain knowledge, we evaluate the general framework for multiple human behaviors modeling with the philosophy of bag of spatiotemporal feature (BoSTF). The brief

[1]  Hsuan-Tien Lin,et al.  A note on Platt’s probabilistic outputs for support vector machines , 2007, Machine Learning.

[2]  Andrew Zisserman,et al.  Oxford TRECVid 2007 \u2013 Notebook paper , 2007, TRECVID.

[3]  Andrew Zisserman,et al.  Oxford TRECVid 2007 - Notebook paper , 2007 .

[4]  Dennis Koelma,et al.  The MediaMill TRECVID 2008 Semantic Video Search Engine , 2008, TRECVID.

[5]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[6]  P. Bartlett,et al.  Probabilities for SV Machines , 2000 .

[7]  Chengjun Liu,et al.  A Gabor feature classifier for face recognition , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[8]  Koen E. A. van de Sande,et al.  Evaluating Color Descriptors for Object and Scene Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Sheng Tang,et al.  TRECVID 2007 High-Level Feature Extraction By MCG-ICT-CAS , 2007, TRECVID.

[10]  Chong-Wah Ngo,et al.  Towards optimal bag-of-features for object categorization and semantic video retrieval , 2007, CIVR '07.

[11]  Alexander G. Hauptmann,et al.  MoSIFT: Recognizing Human Actions in Surveillance Videos , 2009 .

[12]  Pietro Perona,et al.  A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[13]  Jitendra Malik,et al.  Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons , 2001, International Journal of Computer Vision.

[14]  G. Clark,et al.  Reference , 2008 .

[15]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .