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We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast this problem as a manifold clustering problem in which distinct fiber bundles correspond to different submanifolds of the space of orientation distribution functions (ODFs). Our approach integrates tools from sparse representation...
We consider the problem of distributed estimation of the poses of N cameras in a camera sensor network using image measurements only. The relative rotation and translation (up to a scale factor) between pairs of neighboring cameras can be estimated using standard computer vision techniques. However, due to noise in the image measurements, these estimates may not be globally consistent. We address...
Interactive image segmentation traditionally involves the use of algorithms such as graph cuts or random walker. Common concerns with using graph cuts are metrication artifacts (blockiness) and the shrinking bias (bias towards shorter boundaries). The random walker avoids these problems, but suffers from the proximity bias (sensitivity to location of pixels labeled by the user). In this work, we introduce...
Image matting deals with finding the probability that each pixel in an image belongs to a user specified dasiaobjectpsila or to the remaining dasiabackgroundpsila. Most existing methods estimate the mattes for two groups only. Moreover, most of these methods estimate the mattes with a particular bias towards the object and hence the resulting mattes do not sum up to 1 across the different groups....
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