UEC at TRECVID 2012 SIN and MED task

In this paper, we describe our approach and results for the semantics indexing (SIN) task and Multimedia event detection (MED) task at TRECVID2012. In our run of SIN task, we used three features, spatio-temporal (ST) features, SURF and color features. This year, we use all frame to extract features. This run used Multiple Kernel Learning as a fusion method to combine all these features in the same way as last year. Our submitted run is F A UEC1 1. As a result of the full-category SIN task, run reached a performance infAP=0.116. In MED task, we divide videos to shots which are 3000 frames at most and extract SURF, ST features from shots. Then, we select positive shots with VisualRank method from. We get the average of the top three shot scores as the original video score.

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

[2]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[3]  Keiji Yanai,et al.  Extracting Spatio-temporal Local Features Considering Consecutiveness of Motions , 2009, ACCV.

[4]  Shumeet Baluja,et al.  VisualRank: Applying PageRank to Large-Scale Image Search , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[6]  Dong Wang,et al.  Video diver: generic video indexing with diverse features , 2007, MIR '07.

[7]  Paul Over,et al.  Evaluation campaigns and TRECVid , 2006, MIR '06.

[8]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[9]  Manik Varma,et al.  Learning The Discriminative Power-Invariance Trade-Off , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[10]  Shih-Fu Chang,et al.  Kernel Sharing With Joint Boosting For Multi-Class Concept Detection , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[12]  Cor J. Veenman,et al.  Kernel Codebooks for Scene Categorization , 2008, ECCV.

[13]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[14]  Cordelia Schmid,et al.  Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[15]  Meng Wang,et al.  Study on the combination of video concept detectors , 2008, ACM Multimedia.

[16]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[17]  Nello Cristianini,et al.  Learning the Kernel Matrix with Semidefinite Programming , 2002, J. Mach. Learn. Res..

[18]  Keiji Yanai,et al.  A SURF-Based Spatio-Temporal Feature for Feature-Fusion-Based Action Recognition , 2010, ECCV Workshops.