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Mostrar registro sencillo 2009-10-09T13:11:56Z 2009-10-09T03:00:00Z 2009-10
dc.description.abstract There s some very important meaning in the study of realtime face recognition and tracking system for the video monitoring and artifical vision. The current method is still very susceptible to the illumination condition, non-real time and very common to fail to track the target face especially when partly covered or moving fast. In this paper, we propose to use Boosted Cascade combined with skin model for face detection and then in order to recognize the candidate faces, they will be analyzed by the hybrid Wavelet, PCA (principle component analysis) and SVM (support vector machine) method. After that, Meanshift and Kalman filter will be invoked to track the face. The experimental results show that the algorithm has quite good performance in terms of real-time and accuracy. en
dc.format.extent p. 82-88 es
dc.language en es
dc.title Robust realtime face recognition and tracking system en
dc.type Articulo es
sedici.identifier.uri es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Chen, Kai es
sedici.creator.person Zhao, Le Jun es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.other meanshift en
sedici.subject.other Kalman filter es
sedici.subject.other svm en
sedici.subject.other wavelet en
sedici.subject.other realtime face detection en
sedici.subject.other realtime face tracking en
sedici.subject.other face recognition en
sedici.description.fulltext true es Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000005282 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 9, no. 2 es

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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)