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Manifold learning and Sparse Representation Classifier are two popular techniques for face recognition. Because manifold learning can find low-dimensional representations for high-dimensional data, it is widely applied in computer vision and pattern recognition. Most of the manifold learning algorithms can be unified in the graph embedding framework, where the first step is to determine the adjacent...
To detect and recognise hand postures against complex backgrounds, we propose a novel model that is constructed by the integration of image saliency and skin information. Although a skin model is a simple and efficient strategy by which to locate skin regions within images, it is easily affected by complex backgrounds, e.g. skin-like background regions and various lighting conditions. To solve this...
We study the question of hand posture recognition by developing a new class of Bag-of-Features (BoF), namely Hierarchical BoF. The Hierarchical BoF captures spatial information by dividing whole hand area into several sub-regions and projecting local features onto horizontal and vertical directions. A similarity measurement based on Histogram Intersection Kernel (HIK) is proposed to classify hand...
Hand posture is a natural and effective interaction between human and robot. In this paper, we use monocular camera as input device, and an improved Bag-of-Words (BoW) method is proposed to detect and recognize hand posture based on a new descriptor ARPD (Appearance and Relative Position Descriptor) and spectral embedding clustering algorithm. To track hand motion rapidly and accurately, we have designed...
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