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dc.contributor.authorLiu, Yun-Fuen_US
dc.contributor.authorGuo, Jing-Mingen_US
dc.contributor.authorHsia, Chih-Hsienen_US
dc.contributor.authorSu, Sheng-Yaoen_US
dc.contributor.authorLee, Huaen_US
dc.date.accessioned2015-07-21T11:20:46Z-
dc.date.available2015-07-21T11:20:46Z-
dc.date.issued2014-11-01en_US
dc.identifier.issn1556-6013en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TIFS.2014.2355495en_US
dc.identifier.urihttp://hdl.handle.net/11536/123945-
dc.description.abstractFormerly, dimensionality reduction techniques are effective ways for extracting statistical significance of features from their original dimensions. However, the dimensionality reduction also induces an additional complexity burden which may encumber the real efficiency. In this paper, a technique is proposed for the reduction of the dimension of samples rather than the features in the former schemes, and it is able to additionally reduce the computational complexity of the applied systems during the reduction process. This method effectively reduces the redundancies of a sample, in particular for those objects which possess partially symmetric property, such as human face, pedestrian, and license plate. As demonstrated in the experiments, based upon the premises of faster speeds in training and detection by a factor of 4.06 and 1.24, respectively, similar accuracies to the ones without considering the proposed method are achieved. The performance verifies that the proposed technique can offer competitive practical values in pattern recognition related fields.en_US
dc.language.isoen_USen_US
dc.subjectSample refinementen_US
dc.subjectdimension reductionen_US
dc.subjectdata reductionen_US
dc.subjectface detectionen_US
dc.subjectpedestrian detectionen_US
dc.titleSample Space Dimensionality Refinement for Symmetrical Object Detectionen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TIFS.2014.2355495en_US
dc.identifier.journalIEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITYen_US
dc.citation.issue11en_US
dc.citation.spage1953en_US
dc.citation.epage1961en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000344541100001en_US
dc.citation.woscount0en_US
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