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Face Detection Based on Discrete Hidden Markov Models and Singular Value Feature(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2000年05期
Page:
385-389
Research Field:
Publishing date:

Info

Title:
Face Detection Based on Discrete Hidden Markov Models and Singular Value Feature
Author(s):
LiShijin YangJingyu JinZhong
Department of Computer,NUST,Nanjing 210094
Keywords:
imag e processing model building measuring pat tern recognit ion face hidden Markov models( HMM) singular value feature
PACS:
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DOI:
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Abstract:
T his paper presents a novel face detect ion method w hich consist s of tw o algorithms. The f irst one is a f ronta-l view upright face detection algorithm based on the w el-l know n singular value feature ( SVF) and discrete hidden Markov models ( HMM) . The algorithm couples the v irtues of both the SVF and HMM and produces excellent detect ion results. It is tested on a collect ive photo album and has detected the 87. 81 percent of it s 484 people, w hile 537 false alarms are reported. The second one is the extension of the f irst one to rotat ioninvariant face detection. Several HMMs are ut ilized simultaneously and the angle of the ’face’image is obtained. Then the HMM for detecting the upright faces is employed to verify the faceness of the test pat tern. This rotat ion- invariant algorithm is tested on another image set of 173 persons and the detect ion rate is 75. 14 %.

References:

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Last Update: 2013-03-25