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We propose AcFR, an active face recognition system that employs a convolutional neural network and acts consistently with human behaviors in common face recognition scenarios. AcFR comprises two main components—a recognition module and a controller module. The recognition module uses a pre-trained VGG-Face net to extract facial image features along with a nearest neighbor identity recognition algorithm...
Hierarchical dictionary learning seeks multiple dictionaries at different image scales to capture complementary coherent characteristics. We propose a method to learn a hierarchy of two overcomplete synthesis dictionaries with an image classification goal. The classification objective in some sense regularizes the joint optimization of the hierarchical dictionaries and injects refinement feedback...
This paper presents an improved approach for face pose estimation based on depth data using particle swarm optimization (PSO). In this approach, the frontal face of the system-user is first initialized and its depth image is taken as a person-specific template. Each query face of that user is rotated and translated with respect to its centroid using PSO to match with the template. Since the centroid...
This paper proposes a new method to find face in real-time videos by combining detection and tracking. Basically, the method contains two complementary modules: detection by Viola Jones method and tracking by correlation filters. Detection in current frame is independent to previous frames, but the performance may downgrade under harsh conditions in terms of lighting, rotation, occlusion and others...
This paper presents a novel method for rigid surface registration using torchlight structure as data association, and the new method improves the correctness of point matching. When two sets of point clouds are merged, assume a set of torchlight beams parallely pass through them, and each light ray passes the overlapped data twice, one on each set. The Euclidean distance on such pair is taken as measurement...
Over the past few years, multi-view face detection issue has become one of the most attractive research topics in the field of computer vision. In this paper, a novel automatic system for multi-view face detection and pose estimation is proposed. Our approach adopts modified appearance-based learning methods to build corresponding face detectors and pose estimators, and detects multi-view faces according...
This paper proposes a frontal staircase detection algorithm using both classical Haar-like features and a novel set of PCA-base Haar-like features. Real AdaBoost is used for training a cascaded classifier. The PCA-based Haar-like features are extremely efficient at rejecting background regions at early stages in the cascade. A specifically designed scanning scheme made the algorithm constantly time...
Face recognition system usually consists of components of feature extraction and pattern classification. However, not all of extracted facial features contribute to the classification phase positively because of the variations of illumination and poses in face images. In this paper, a three-step feature selection algorithm is proposed in which discrete cosine transform (DCT) and genetic algorithms...
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