We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
In this paper, we formulate an algorithm for the stereo matching problem with careful handling of disparity, discontinuity and occlusion. The algorithm works with a global matchin...
Qingxiong Yang, Liang Wang, Ruigang Yang, Henrik S...
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...
We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with...
The wavelet transform hierarchically decomposes images with prescribed bases, while multilineal models search for optimal bases to adapt visual data. In this paper, we integrate t...