DSpace Repository

Rotation Invariant Real-time Face Detection and Recognition System

Show simple item record

dc.creator Ho, Purdy
dc.date 2004-10-20T20:48:40Z
dc.date 2004-10-20T20:48:40Z
dc.date 2001-05-31
dc.date.accessioned 2013-10-09T02:48:26Z
dc.date.available 2013-10-09T02:48:26Z
dc.date.issued 2013-10-09
dc.identifier AIM-2001-010
dc.identifier CBCL-197
dc.identifier http://hdl.handle.net/1721.1/7171
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.
dc.format 24 p.
dc.format 12501066 bytes
dc.format 896203 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-2001-010
dc.relation CBCL-197
dc.subject AI
dc.subject vision
dc.title Rotation Invariant Real-time Face Detection and Recognition System


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account