We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
We study the problem of finding an outlier-free subset of a set of points (or a probability distribution) in n-dimensional Euclidean space. As in [BFKV 99], a point x is defined t...
To facilitate accurate and efficient detection of motion
patterns in video data, it is desirable to abstract from pixel
intensity values to representations that explicitly and co...
This paper presents a sparse representation of 2D planar shape through the composition of warping functions, termed formlets, localized in scale and space. Each formlet subjects t...
Abstract. Concepts from elasticity are applied to analyze modes of variation on shapes in two and three dimensions. This approach represents a physically motivated alternative to s...