Real-Time Person Identification System for Intelligent Digital TV

Intelligent digital TV (iDTV) is an enhanced digital TV that can automatically provide user-personalized services for each audience. For the user-personalized services, the iDTV should recognize audiences in real-time. Thus, in this paper, we define a novel structure of the iDTV and propose a real-time person identification system embedded in the iDTV. The proposed system consists of three phases: preprocessing for reducing computational costs of the proposed system, face detection using a statistical approach with Haar-like features, and face recognition using Support Vector Machines (SVMs). Experimental results show that the proposed system achieves efficient performance with high recognition accuracy of above 90% at the speed of 15~20 fps, which is suitable for applying to the iDTV.