Spatio-temporal Tube Kernel For Actor Retrieval

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.

• Type: Conference
• Year: 2009
• Where: ICIP
• Keywords: Actor Retrieval Task, Actor Video Retrieval, ICIP 2009, Image Processing, Spatio-temporal Tubes