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To study the robustness of face recognition algorithms on conditions of complex illumination, facial expression and posture, three subset databases (Illumination, Expression and Posture subsets) are constructed by selecting images from several existing face databases. Advantages and disadvantages of seven typical algorithms on extracting global and local features are discussed respectively through...
Expression variation is one of the most important factors that considerably influence the performance of face recognition. In order to enhance robustness to expression variations, a procedure of 3D face recognition based on depth image and SURF Operator is proposed. We use Fisher Linear Discriminant (FLD) method on the depth image to perform coarse recognition first to catch the highly ranked 3D faces...
An approach of 3D face recognition by using of facial surface classification image and PCA is presented. In the step of pre-processing, the scattered 3D points of a facial surface are normalized by surface fitting algorithm using multilevel B-splines approximation. Then, partial-ICP method is utilized to adjust 3D face model to be in the right front pose for a better recognition performance. By using...
Feature extraction is crucial for face recognition. A new method of face feature extraction based on Speeded-Up Robust Feature (SURF) is proposed in this paper. SURF is invariant of shifting, rotation and scaling, and partially invariant of illumination and affine transformation. We use Fisher Linear Discriminant (FLD) method to extract the quadratic features on the basis of SURF feature, then measure...
A composite algorithm is proposed to identify the opened and shut states of eye in real-time video. Sequentially, each frame of the video is processed first to find and separate the eye regions; then, the accumulation array of circular Hough transform is applied for detecting circles to recognize the opened state of the eye, and the upper eyelid curve is calculated to identify its bending direction...
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