This paper investigates how to boost region-based image segmentation by pursuing a new
solution to fuse multiple types of image features. A collaborative image segmentation …

Segmenting a single image into multiple coherent groups remains a challenging task in the
field of computer vision. Particularly, spectral segmentation which uses the global …

We present an approach to visual tracking based on dividing a target into multiple regions,
or fragments. The target is represented by a Gaussian mixture model in a joint feature …

Finite mixture model based on the Student's-t distribution, which is heavily tailed and more
robust than Gaussian, has recently received great attention for image segmentation. A new …

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general
spatially-or temporally-dependent data, imposing the belief that proximate data are more …

We present a novel interactive image segmentation approach with user scribbles using
constrained Laplacian graph optimization. A novel energy framework is developed by …

The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian
mixture model, has recently received great attention on image processing. In this paper, we …

This paper presents a new and simple segmentation method based on the K-means
clustering procedure and a two-step process. The first step relies on an original de-texturing …

A new accurate and robust non-rigid point set registration method, named DSMM, is
proposed for non-rigid point set registration in the presence of significant amounts of missing …

A novel superpixel extraction algorithm using a higher order energy optimization framework
is proposed in this paper. We first adopt the k-means clustering technique to quickly get an …