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dc.contributor.authorFu, HCen_US
dc.contributor.authorLai, PSen_US
dc.contributor.authorLou, RSen_US
dc.contributor.authorPao, HTen_US
dc.date.accessioned2014-12-08T15:27:05Z-
dc.date.available2014-12-08T15:27:05Z-
dc.date.issued2000en_US
dc.identifier.isbn0-7803-6278-0en_US
dc.identifier.urihttp://hdl.handle.net/11536/19311-
dc.description.abstractThis paper presents a neural network based scheme for human face detection and eye localization in color images under non-constrained scene. A Self-growing Probabilistic Decision-based Neural Network (SPDNN) is used to learn the conditional distribution for each color classes. Pixels of a color image are first classified into facial or non-facial regions, then pixels in the facial region are followed by eye region segmentation. The class of each pixel is determined by using the conditional distribution of the chrominance components of pixels belonging to each class. The paper demonstrates a successful application of SPDNN to face detection and eye localization on a database of 755 images from 151 persons. Regarding the performance, experimental results are elaborated in Section 3. As to the processing speed, the face detection and eye localization processes consume approximately 560 ms on a Pentium-II personal computer.en_US
dc.language.isoen_USen_US
dc.subjectcolor segmentationen_US
dc.subjectface detectionen_US
dc.subjecteye localizationen_US
dc.titleFace detection and eye localization by neural network based color segmentationen_US
dc.typeProceedings Paperen_US
dc.identifier.journalNEURAL NETWORKS FOR SIGNAL PROCESSING X, VOLS 1 AND 2, PROCEEDINGSen_US
dc.citation.spage507en_US
dc.citation.epage516en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000166276900052-
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