Kernel-Coeﬃcient Based Feature for Face-Detection

dc.contributor.author	Mortuza, Fahad Bin
dc.date.accessioned	2017-10-02T06:52:24Z
dc.date.available	2017-10-02T06:52:24Z
dc.date.issued	4/13/2017
dc.identifier.uri	http://dspace.ewubd.edu/handle/2525/2319
dc.description	This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh.	en_US
dc.description.abstract	We propose a novel appearance based feature method for face detection using rigid kernel (template) and its coeﬃcients. The proposed features respond to pixels of edges of an object(face/non-face) with respect to the kernel as its coeﬃcients are arranged in a certain order to generate values for better classiﬁcation in SVMs (Support Vector Machines). The proposed method manipulates the symmetric appearance of a face with respect to a rigid kernel(template).	en_US
dc.language.iso	en_US	en_US
dc.publisher	East West University	en_US
dc.relation.ispartofseries	;00101 CSE
dc.subject	Kernel-Coeﬃcient Based Feature	en_US
dc.title	Kernel-Coeﬃcient Based Feature for Face-Detection	en_US
dc.type	Thesis	en_US