Audio-Visual Classification Video Browser

This paper presents our third participation in the Video Browser Showdown. Building on the experience that we gained while participating in this event, we compete in the 2014 showdown with a more advanced browsing system based on incorporating several audio-visual retrieval techniques. This paper provides a short overview of the features and functionality of our new system.

[1]  Markus Schedl,et al.  The MediaEval 2013 Affect Task: Violent Scenes Detection , 2013, MediaEval.

[2]  Chih-Jen Lin,et al.  LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..

[3]  R. Tibshirani,et al.  Least angle regression , 2004, math/0406456.

[4]  Marcus Jerome Pickering,et al.  Evaluation of key frame-based retrieval techniques for video , 2003, Comput. Vis. Image Underst..

[5]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[6]  Alexei A. Efros,et al.  Data-driven visual similarity for cross-domain image matching , 2011, ACM Trans. Graph..

[7]  Chih-Jen Lin,et al.  Probability Estimates for Multi-class Classification by Pairwise Coupling , 2003, J. Mach. Learn. Res..

[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]  Guillermo Sapiro,et al.  Online Learning for Matrix Factorization and Sparse Coding , 2009, J. Mach. Learn. Res..

[10]  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.

[11]  Alan F. Smeaton,et al.  DCU at MMM 2013 Video Browser Showdown , 2013, MMM.

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