CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Statistical learning of evaluation function for ASM/AAM image alignment
Huang, XS; Li, SZ; Wang, YS; Maltoni, D; Jain, AK
Source PublicationBIOMETRIC AUTHENTICATION, PROCEEDINGS
2004
Volume3087Pages:45-56
SubtypeArticle
AbstractAlignment between the input and target objects has great impact on the performance of image analysis and recognition system, such as those for medical image and face recognition. Active Shape Models (ASM)[1] and Active Appearance Models (AAM) [2, 3] provide an important framework for this task. However, an effective method for the evaluation of ASM/AAM alignment results has been lacking. Without an alignment quality evaluation mechanism, a bad alignment cannot be identified and this can drop system performance.
WOS HeadingsScience & Technology ; Technology
Indexed ByISTP ; SCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000223074400005
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7953
Collection模式识别国家重点实验室_生物识别与安全技术研究
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
2.Microsoft Res Asia, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Huang, XS,Li, SZ,Wang, YS,et al. Statistical learning of evaluation function for ASM/AAM image alignment[J]. BIOMETRIC AUTHENTICATION, PROCEEDINGS,2004,3087:45-56.
APA Huang, XS,Li, SZ,Wang, YS,Maltoni, D,&Jain, AK.(2004).Statistical learning of evaluation function for ASM/AAM image alignment.BIOMETRIC AUTHENTICATION, PROCEEDINGS,3087,45-56.
MLA Huang, XS,et al."Statistical learning of evaluation function for ASM/AAM image alignment".BIOMETRIC AUTHENTICATION, PROCEEDINGS 3087(2004):45-56.
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