Abstract :
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
Keywords :
computational complexity; face recognition; image matching; image sequences; multimedia computing; video signal processing; automated face annotation; automated video authoring; computational time; content-based face retrieval; face expression; face sequences; high-dimensional index structure; lighting conditions; multimedia applications; performance; pose; robust matching; scalability; videos; Data mining; Detectors; Electrical capacitance tomography; Eyes; Face detection; Motion pictures; Read only memory; Robustness; Skin; Videos;
