Paper
18 May 2004 Block-based face detection scheme using face color and motion information
Soohyun Kim, Sunghyun Lim, Hyungtai Cha, Hernsoo Hahn
Author Affiliations +
Proceedings Volume 5297, Real-Time Imaging VIII; (2004) https://doi.org/10.1117/12.526332
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
Abstract
This paper proposes a new approach of fusing skin color and motion information to detect face areas in moving pictures. For reducing the computation time and also the effect of lighting conditions, the block based analysis technique is used in the fusion process. Motion is detected from a difference image segmented into blocks having 4x4 pixels, and a block is classified as a MB (motion block) if the sum of pixel values in the blocks is larger than a specific threshold. Similarly, each block is marked as a FB (face block) if it contains more than one skin color pixels. Then the candidates for face regions (CF) are selected by fusing MB and FB images using the logical AND operation. Among CFs, the face regions are selected by using the heuristic rules on human faces such as the ratio of width and height, the high frequency portion in a face region, etc. In the final step, the selected CFs are tested by the facial feature scoring scheme which selects the CF having a score larger than a threshold as a face. The experimental results have shown that the proposed algorithm determines face regions in 0.08 sec with the correct decision rate of 91.7% and false detection rate 4.26%.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Soohyun Kim, Sunghyun Lim, Hyungtai Cha, and Hernsoo Hahn "Block-based face detection scheme using face color and motion information", Proc. SPIE 5297, Real-Time Imaging VIII, (18 May 2004); https://doi.org/10.1117/12.526332
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CITATIONS
Cited by 4 scholarly publications and 1 patent.
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KEYWORDS
Mouth

Facial recognition systems

Light sources and illumination

Eye

Skin

Image segmentation

Motion detection

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