Video Copy Detection Using Inclined Video Tomography and Bag-of-Visual-Words

Techniques for video fingerprinting are helpful in managing vast libraries of video clips. Recent advances have shown that video tomography and Bag-of-Visual-Words (BoVW) can be successfully used for the purpose of video fingerprinting. In this paper, we introduce a novel video signature (i.e., a novel video fingerprint) that takes advantage of both video tomography and BoVW. Specifically, the proposed video signature is created by first extracting inclined tomography images from the video content, and by subsequently applying the BoVW approach to the inclined tomography images obtained. The key to our approach is that we make the angle of inclination of the tomography images dependent on the amount of motion in the video content. That way, the proposed video signature is able to capture both spatial and temporal information. Experimental results obtained for the publicly available TREVID-2009 video set indicate that video copy detection by means of the proposed video signature is robust against spatial and temporal transformations.

[1]  Jiwu Huang,et al.  Salient covariance for near-duplicate image and video detection , 2011, 2011 18th IEEE International Conference on Image Processing.

[2]  Chong-Wah Ngo,et al.  On the Annotation of Web Videos by Efficient Near-Duplicate Search , 2010, IEEE Transactions on Multimedia.

[3]  Olivier Buisson,et al.  Content-Based Copy Retrieval Using Distortion-Based Probabilistic Similarity Search , 2007, IEEE Transactions on Multimedia.

[4]  Cordelia Schmid,et al.  A maximum entropy framework for part-based texture and object recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[5]  Miroslaw Bober,et al.  Recent developments on standardisation of MPEG-7 Visual Signature Tools , 2010, 2010 IEEE International Conference on Multimedia and Expo.

[6]  Paul Over,et al.  TRECVID 2009 -- Goals, Tasks, Data, Evaluation Mechanisms and Metrics | NIST , 2010 .

[7]  Christian Petersohn.  Fraunhofer HHI at TRECVID 2004: Shot Boundary Detection System , 2004, TRECVID.

[8]  Athman Bouguettaya,et al.  An Efficient Near-Duplicate Video Shot Detection Method Using Shot-Based Interest Points , 2009, IEEE Transactions on Multimedia.

[9]  Nuria Oliver,et al.  Looking at near-duplicate videos from a human-centric perspective , 2010, ACM Trans. Multim. Comput. Commun. Appl..

[10]  Yoshinobu Tonomura,et al.  Video tomography: an efficient method for camerawork extraction and motion analysis , 1994, MULTIMEDIA '94.

[11]  Sang Hyun Kim,et al.  An efficient algorithm for video sequence matching using the modified Hausdorff distance and the directed divergence , 2002, IEEE Trans. Circuits Syst. Video Technol..

[12]  Hung-Khoon Tan,et al.  Near-Duplicate Keyframe Identification With Interest Point Matching and Pattern Learning , 2007, IEEE Transactions on Multimedia.

[13]  Chu-Song Chen,et al.  A Framework for Handling Spatiotemporal Variations in Video Copy Detection , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Borko Furht,et al.  Video identification using video tomography , 2009, 2009 IEEE International Conference on Multimedia and Expo.

[15]  Parham Aarabi,et al.  Tiny Videos: A Large Data Set for Nonparametric Video Retrieval and Frame Classification , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  B. S. Manjunath,et al.  Introduction to mpeg-7 , 2002 .

[17]  Shree K. Nayar,et al.  Ordinal Measures for Image Correspondence , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

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

[19]  Trevor Darrell,et al.  The pyramid match kernel: discriminative classification with sets of image features , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[20]  Wesley De Neve,et al.  Bimodal fusion of low-level visual features and high-level semantic features for near-duplicate video clip detection , 2011, Signal Process. Image Commun..

[21]  Li Chen,et al.  Video copy detection: a comparative study , 2007, CIVR '07.

[22]  Pietro Perona,et al.  One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.