Towards an automatic face indexing system for actor-based video services in an IPTV environment

Automatic face indexing is an important technique for realizing actor-based video services in an IPTV environment. This paper proposes a novel face indexing system that takes advantages of the internet connection of an STB to construct a FR engine that is equipped with a high number of training face images. In addition, we use a face clustering technique to obtain multiple face images of the same subject from a sequence of video frames. The clustered face images are combined using a weighted feature fusion scheme, resulting in a considerable enhancement in face indexing accuracy. The effectiveness of the proposed system is validated using more than 300,000 video frames, collected from five video clips containing drama or movie content. The experimental results show that the proposed system can achieve a face annotation accuracy that is feasible for practical applications.

[1]  Yunhong Wang,et al.  Face indexing and searching from videos , 2008, 2008 15th IEEE International Conference on Image Processing.

[2]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Motorola Labs , 2022 .

[4]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[5]  Konstantinos N. Plataniotis,et al.  Regularized discriminant analysis for the small sample size problem in face recognition , 2003, Pattern Recognit. Lett..

[6]  George Karypis,et al.  Hierarchical Clustering Algorithms for Document Datasets , 2005, Data Mining and Knowledge Discovery.

[7]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[8]  Luis Torres,et al.  Automatic face recognition for video indexing applications , 2002, Pattern Recognit..

[9]  Wei-Ta Chu,et al.  RoleNet: Movie Analysis from the Perspective of Social Networks , 2009, IEEE Transactions on Multimedia.

[10]  Wen Gao,et al.  Hierarchical Ensemble of Global and Local Classifiers for Face Recognition , 2009, IEEE Trans. Image Process..

[11]  Jie Wang,et al.  On solving the face recognition problem with one training sample per subject , 2006, Pattern Recognit..

[12]  David Masip,et al.  Boosted Online Learning for Face Recognition , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Ding-Zhu Du,et al.  A Decision Criterion for the Optimal Number of Clusters in Hierarchical Clustering , 2003, J. Glob. Optim..

[14]  Sang Heun Shim,et al.  Real-time shot boundary detection for digital video camera using the MPEG-7 descriptor , 2002, IS&T/SPIE Electronic Imaging.

[15]  Zhu Liu,et al.  Uninterrupted Recording and Real Time Content-Based Indexing Service for IPTV Systems , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.

[16]  Jonathan Warrell,et al.  Tied Factor Analysis for Face Recognition across Large Pose Differences , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Steven Verstockt,et al.  Actor recognition for interactive querying and automatic annotation in digital video , 2009, Internet, Multimedia Systems and Applications.

[18]  Oliver Friedrich,et al.  The future of TV and media services - Interactive live demo of Fraunhofer FOKUS standardized converged Rich Media and IPTV solution , 2009, 2009 10th International Conference on Telecommunications.

[19]  Narendra Ahuja,et al.  Detecting Faces in Images: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Yong Man Ro,et al.  Color Face Recognition for Degraded Face Images , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[21]  Ali C. Begen,et al.  IPTV and video networks in the 2015 timeframe: The evolution to medianets , 2009, IEEE Communications Magazine.

[22]  Arun Ross,et al.  Score normalization in multimodal biometric systems , 2005, Pattern Recognit..

[23]  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.

[24]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.