A Novel Face Detection Technique Using Depth Information and Active Shape Models

碩士 === 開南大學 === 資訊管理學系 === 101 === In computer vision, many methods employ color images to detect human faces. But it is easy affected by surrounding factors and brightness. Then the object of face positions may errors. Recently, Microsoft has presented an interaction sensor which called Kinect. It...

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Bibliographic Details
Main Authors:	Ting-Wen Chen, 陳鼎文
Other Authors:	Kuo-Ming, Hung
Format:	Others
Language:	zh-TW
Published:	2013
Online Access:	http://ndltd.ncl.edu.tw/handle/85507086155236096616

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record_format	oai_dc
spelling	ndltd-TW-101KNU003960102015-10-13T22:18:46Z http://ndltd.ncl.edu.tw/handle/85507086155236096616 A Novel Face Detection Technique Using Depth Information and Active Shape Models 使用深度資訊與主動式形狀模型之人臉定位技術 Ting-Wen Chen 陳鼎文碩士開南大學資訊管理學系 101 In computer vision, many methods employ color images to detect human faces. But it is easy affected by surrounding factors and brightness. Then the object of face positions may errors. Recently, Microsoft has presented an interaction sensor which called Kinect. It can output the range between object and sensor from infrared ray controller to produce the depth image. The depth image against most of surrounding brightness, and be used to increase the accuracy in object recognition. In this paper, we employ Kinect to capture color and depth image. After then we detect the face blocks by ASM. When faces were detected, we compare the face object size between detection and table we count distance in depth image. Finally, remove the error blocks to increase the detection accuracy from ASM. Experiment result shows our method not only removes the error blocks successfully, but also makes ASM detection higher accuracy. And we proposed the table that count distance will be used in future work. Kuo-Ming, Hung 洪國銘 2013 學位論文 ; thesis 38 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 開南大學 === 資訊管理學系 === 101 === In computer vision, many methods employ color images to detect human faces. But it is easy affected by surrounding factors and brightness. Then the object of face positions may errors. Recently, Microsoft has presented an interaction sensor which called Kinect. It can output the range between object and sensor from infrared ray controller to produce the depth image. The depth image against most of surrounding brightness, and be used to increase the accuracy in object recognition. In this paper, we employ Kinect to capture color and depth image. After then we detect the face blocks by ASM. When faces were detected, we compare the face object size between detection and table we count distance in depth image. Finally, remove the error blocks to increase the detection accuracy from ASM. Experiment result shows our method not only removes the error blocks successfully, but also makes ASM detection higher accuracy. And we proposed the table that count distance will be used in future work.
author2	Kuo-Ming, Hung
author_facet	Kuo-Ming, Hung Ting-Wen Chen 陳鼎文
author	Ting-Wen Chen 陳鼎文
spellingShingle	Ting-Wen Chen 陳鼎文 A Novel Face Detection Technique Using Depth Information and Active Shape Models
author_sort	Ting-Wen Chen
title	A Novel Face Detection Technique Using Depth Information and Active Shape Models
title_short	A Novel Face Detection Technique Using Depth Information and Active Shape Models
title_full	A Novel Face Detection Technique Using Depth Information and Active Shape Models
title_fullStr	A Novel Face Detection Technique Using Depth Information and Active Shape Models
title_full_unstemmed	A Novel Face Detection Technique Using Depth Information and Active Shape Models
title_sort	novel face detection technique using depth information and active shape models
publishDate	2013
url	http://ndltd.ncl.edu.tw/handle/85507086155236096616
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A Novel Face Detection Technique Using Depth Information and Active Shape Models

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