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Accurately and reliably tracking the 3D position and orientation of individuals in large flying swarms is valuable not only for scientific researches but also practical applications. However, large quantity, frequent occlusions, similar appearance, tiny body size and abrupt motion make it remain an open problem. The 3D flying swarm tracking method proposed in this paper tracks both position and orientation...
In this paper, we present an algorithm to infer foreground segmentation from given a sequence of images. In our system, we can capture the interested object on a planar background with a handheld camera. There are two main assumptions are mentioned: 1) the region of interest appears entirely in all images; 2) the background pixels have a similar plane projective transformation, i.e., the foreground...
A novel multi-attribute sparse representation enforced with group constraints is proposed in this paper. Data with multiple attributes can be represented by individual binary matrices to indicate the group properties for each data sample. Then, these attribute matrices are incorporated into the formulation of l1-minimization. The solution is obtained by jointly considering the data reconstruction...
The reduction of speckle in SAR image is necessary for processing of SAR image such as feature detection and extraction. In Contourlet transform, a drawback of Laplacian pyramid (LP) is implicit oversampling and non-orthogonal decomposition, Wavelet transform is a critically sampled scheme but it only generated three direction. Taking advantage of Wavelet and Contourlet, the proposed method is complemented...
A semi-automatic 3D roof reconstruction method is proposed in this paper. It consists of two components: automatic recognition of 2D plane drawings and interactively ldquopullingrdquo or ldquopushingrdquo the recognized results. Only a limited number of reconstruction operations are needed to generate various types of 3D roofs, making the method efficient.
In this paper we propose an hierarchical Markov random field (HMRF) model and the Bayesian estimation frame for separating noisy linear mixtures of images constituted by homogeneous patches. A latent Potts-Markov labeling field is introduced for each source image to enforce piecewise homogeneity of pixel values. Based on classification labels, the upper observable intensity field is modeled by the...
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