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Motion segmentation is an important research field as it forms the stepping stone for traffic monitoring, video surveillance, activity analysis, gait recognition and many other automatic imaging applications. In this work, a novel generic multiresolution (MR) based framework has been proposed in conjunction with Sigma-delta based motion segmentation algorithm. The framework provides a general platform...
Moving objects detection is one basic problem in computer vision and various methods have been proposed. However, the performance of these methods may be deteriorated by the moving shadows. In this paper we present a novel method for the moving shadow detection. Based on the analysis of the illumination model, we prove that the normalized eigenvalue of image block is illumination invariant. The distribution...
A new focus measure system is proposed based on complex wavelet transform and quadrature pair of steerable filters. In shape from focus (SFF), noise, illumination variation and oriented features degrade the performance of focus measure operator. This paper introduces the use of complex wavelets due to shift-invariance and directionality of the transformation suitable for detecting various types of...
We present a novel multiresolution analysis based stereo matching method using curvelets and modified adaptive support weight. Multiresolution analysis has long been applied to stereo correspondence. However, previous methods suffer from false matches arising from textureless region or repetitive textures and fattening effect due to area based matching. In the proposed approach, we have reduced false...
Salient object detection is a basic technique for many computer vision applications. In this paper, we propose an adaptive computational model to detect the salient object in color images. Firstly, three human observation behaviors and scalable subtractive clustering techniques are used to construct attention Gaussian mixture model (AGMM) and background Gaussian mixture model (BGMM). Secondly, the...
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