Spatio-temporal Tube Kernel for Actor Retrieval

Shuji Zhao 1 Frédéric Precioso 1 Matthieu Cord 2
1 MIDI - Multimedia Indexation and Data Integration
ETIS - Equipes Traitement de l'Information et Systèmes
2 MALIRE - Machine Learning and Information Retrieval
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : This paper presents an actor video retrieval system based on face video-tubes extraction and representation with sets of temporally coherent features. Visual features, SIFT points, are tracked along a video shot, resulting in sets of feature point chains (spatio-temporal tubes). These tubes are then classified and retrieved using a kernel-based SVM learning framework for actor retrieval in a movie. In this paper, we present optimized feature tubes, we extend our feature representation with spatial location of SIFT points and we describe the new Spatio-Temporal Tube Kernel (STTK) of our contentbased retrieval system. Our approach has been tested on a real movie and proved to be faster and more robust for actor retrieval task.
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Shuji Zhao, Frédéric Precioso, Matthieu Cord. Spatio-temporal Tube Kernel for Actor Retrieval. 16th IEEE International Conference on Image Processing (ICIP 09), Nov 2009, Cairo, Egypt. pp.1885-1888, ⟨10.1109/ICIP.2009.5413540⟩. ⟨hal-00773044⟩

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