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This paper presents a novel approach to detecting the presence of objects in a scene from the 3D sparse disparity space obtained by stereo matching. The use of stereo imaging makes the proposed method particularly useful for detecting stationary objects without the need of learning the appearance patterns on an object or the background. Our approach is based on the fact that sparse image features...
This paper presents a set of algorithms for vehicle detection in large scale aerial images. Vehicles are detected based on geometric and radiometric features, extracted within a multiresolution linear Gaussian scale-space. The image features, described by their local structures, are classified using support vector machines. Classified features are then clustered by an unsupervised affine propagation...
Moving objects detection is a fundamental step in many vision based applications. Background subtraction is the typical method. Many background models have been introduced to deal with different problems. The method based on mixture of Gaussians is a good balance between accuracy and complexity, and is used frequently by many researchers. But it still cannot provide satisfied results in some cases...
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