Nanjing University in TRECVID 2010

This report describes the details of our system for copy detection task in TRECVID 2009. We submitted 4 runs, 2 for video-only queries and 2 for video + audio queries. Details are listed below. Each group is with same technique but different parameters.

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

[2]  Jing Huang,et al.  Color-Spatial Image Indexing and Applications , 1998 .

[3]  Tao Liu,et al.  AT&T Research at TRECVID 2009 Content-based Copy Detection , 2009, TRECVID.

[4]  Horst Bischof,et al.  Efficient Maximally Stable Extremal Region (MSER) Tracking , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[5]  Justin Zobel,et al.  Clustering near-duplicate images in large collections , 2007, MIR '07.

[6]  Michael Isard,et al.  Bundling features for large scale partial-duplicate web image search , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[7]  David G. Lowe,et al.  Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration , 2009, VISAPP.

[8]  Gabriela Csurka,et al.  Visual categorization with bags of keypoints , 2002, eccv 2004.

[9]  Alexandr Andoni,et al.  Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions , 2006, 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06).

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

[11]  Robin Hess.  An Open-Source SIFT Library , 2010 .

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

[13]  Hai Tao,et al.  Representing Images Using Nonorthogonal Haar-Like Bases , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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