Titlebook: Biometric Recognition; 9th Chinese Conferen Zhenan Sun,Shiguang Shan,Weiqi Yuan Conference proceedings 2014 Springer International Publishi

生意行为

Thermal Infrared Face Recognition Based on the Modified Blood Perfusion Model and Improved Weber Local descriptor is proposed. Weber local descriptor (WLD) is able to extract a wealth of local texture information, which computes not only the differences between the center pixel and its neighbors but also the gradient orientation information describing the direction of edges in the local area, so i

变态

Research of Improved Algorithm Based on LBP for Face Recognitionhis paper, a research on the classical Local Binary Pattern (LBP) is made and an improved algorithm named double-circle LBP is proposed, which can further enhance the rotation invariant characteristic of LBP. Since LBP descriptor based on the block has good recognition effect, this paper further pro

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A Real-Time Face Recognition System Based on IP Camera and SRC Algorithmresearch on the IP camera and rewrite some function of SDK so that OpenCV can process the video frame. First, AdaBoost algorithm is used to detect face in each frame, and then LBP is used to extract the feature of texture. Finally, we obtain the result by SRC algorithm. Experimental results show tha

ligature

irreducible

Multi-Task Learning for Face Ethnicity and Gender Recognitiond gender recognition with face images. The proposed FS-MTL selects the common features which are shared by multi-tasks are based on the sparse optimization solution of group Least Absolute Shrinkage and Selection Operator (LASSO). Compared with either the classic feature selection algorithm or the s

objection

A Unified Facial Feature Pointdatabasedatabases with large amount of images available with increasing research on face analysis, there are few open large face databases with the coordinates of multiple Facial Feature Points (FFPs) provided. In this paper, we build up a large FFP database combining several existing face databases through

刚毅

有危险

FEAS

演绎

Biometric Recognition978-3-319-12484-1Series ISSN 0302-9743 Series E-ISSN 1611-3349