Real-time approach to recognizing the human face in poor-quality video

Zhaoyang Chen; Guilin Zhang; Ming Jiang

doi:10.1117/12.441479

21 September 2001 Real-time approach to recognizing the human face in poor-quality video

Zhaoyang Chen, Guilin Zhang, Ming Jiang

Proceedings Volume 4550, Image Extraction, Segmentation, and Recognition; (2001) https://doi.org/10.1117/12.441479
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

This paper focuses on an effective face recognition algorithm of poor quality video data and its real-time implementation. As the fundamental step of our approach, a fast face detection method based on color information is presented. Instead of performing a pixel-based color segmentation on each single face image, we incorporate color information into a face detection scheme based on spatio-temporal filtering in image sequences, which can reduce the noises in surveillance video. Our face recognition method is based on principal component analysis (PCA) that is fairly effective and fast for surveillance video in comparison with feature-based methods. For the training set, a large database of numerous face images of each subjects, digitized at the condition of three head orientations is setup. We use separate eigenspaces for different views of head orientations, so that the collection of images taken from each view of head orientations will have its own eigenspace. For real-time implementation, a automatic face detection and recognition system with TI Digital Signal Processor(DSP) TMS320C6201 is described.

Citation Download Citation

Zhaoyang Chen, Guilin Zhang, and Ming Jiang "Real-time approach to recognizing the human face in poor-quality video", Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); https://doi.org/10.1117/12.441479

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KEYWORDS

Facial recognition systems

Video

Video surveillance

Image quality

Image segmentation

Surveillance

Head

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