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Coding videophone sequences at a bet...
~
Cascante, Eduardo Cardoce.
Coding videophone sequences at a better perceptual quality by using face detection and MPEG coding.
紀錄類型:
書目-電子資源 : 單行本
正題名/作者:
Coding videophone sequences at a better perceptual quality by using face detection and MPEG coding./
作者:
Cascante, Eduardo Cardoce.
面頁冊數:
83 p.
附註:
Source: Masters Abstracts International, Volume: 45-02, page: 0906.
Contained By:
Masters Abstracts International45-02.
標題:
Engineering, Electronics and Electrical. -
電子資源:
Download PDF (下載PDF全文)
ISBN:
9780542923784
Coding videophone sequences at a better perceptual quality by using face detection and MPEG coding.
Cascante, Eduardo Cardoce.
Coding videophone sequences at a better perceptual quality by using face detection and MPEG coding.
- 83 p.
Source: Masters Abstracts International, Volume: 45-02, page: 0906.
Thesis (M.S.)--University of Kansas, 2006.
This paper addresses our proposed method to improve the compression rate of a typical videophone sequence encoded using the MPEG standard, by using Region of Interest Coding, while minimizing the loss of perceptual quality. Thus we present a new technique for face detection at a block level, based on skin color segmentation using the HSI color space and edge detection, to identify the region of interest in the sequence. Furthermore, we introduce a selective smoothing technique to smooth those regions belonging to the background that are less relevant to the eye and therefore reduce storage requirements. The performance of our algorithm in terms of speed and accuracy is demonstrated by experimental results.
ISBN: 9780542923784Subjects--Topical Terms:
170927
Engineering, Electronics and Electrical.
Coding videophone sequences at a better perceptual quality by using face detection and MPEG coding.
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This paper addresses our proposed method to improve the compression rate of a typical videophone sequence encoded using the MPEG standard, by using Region of Interest Coding, while minimizing the loss of perceptual quality. Thus we present a new technique for face detection at a block level, based on skin color segmentation using the HSI color space and edge detection, to identify the region of interest in the sequence. Furthermore, we introduce a selective smoothing technique to smooth those regions belonging to the background that are less relevant to the eye and therefore reduce storage requirements. The performance of our algorithm in terms of speed and accuracy is demonstrated by experimental results.
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Download PDF (下載PDF全文)
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