Scalable reduced dimension face object segmentation and tracking

Lei Zhang; Guo-Fang Tu

doi:10.1117/12.539029

25 September 2003 Scalable reduced dimension face object segmentation and tracking

Lei Zhang, Guo-Fang Tu

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539029
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

Abstract

SScalable reduced dimension face object segmentation and tracking (SRDOST) based on wavelet is presented in this paper. SRDOST algorithm is taken advantage of the characteristic of wavelet coefficeints multiresolution in the same direction, which makes SRDOST be applied to detect and track the video object of a reduced dimension image with much lower complexity and more sufficient accuracy. The number of image data at the lowest frequency subband is about one of (2^level)² to that of the original image so that the detection complexity at the lowest frequency subband may reduce greatly. It is important that SRDOST may be a multiresolution object segmentation algorithm based on wavelet transform, which may bring a family of video object sequence (VOS) with different resolutions. So SRDOST is a low complexity and efficient object segmentation algorithm. The proposed algorithm is to be integrated with our video object based wavelet color video coding with motion compensation algorithm.

Citation Download Citation

Lei Zhang and Guo-Fang Tu "Scalable reduced dimension face object segmentation and tracking", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539029

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