An efficient implementation and evaluation of robust face sequence matching

This paper presents a robust and efficient matching method for face sequences obtained from videos. Face information is quite important especially for news programs, dramas, and movies. Face sequence matching for such videos enables many multimedia applications including content-based face retrieval, automated face annotation, automated video authoring, etc. However face sequences in videos are subject to variations in lighting conditions, pose, face expression, etc., which cause difficulty in face matching. These problems are tackled to achieve robust face sequence matching applicable to real video domains, and its efficient implementation is presented. The paper proves the proposed method achieves good performance in actual video domains. In addition, by combination with the high-dimensional index structure, the algorithm achieves practical computational time, as well as scalability against increase of the number of faces.