Automatic segmentation of nuclei in 3D microscopy images is essential for many biological studies including high throughput analysis of gene expression level, morphology, and phen...
Abstract. We propose a new generative model, and a new image similarity kernel based on a linked hierarchy of probabilistic segmentations. The model is used to efficiently segment ...
In this paper, we will first introduce a novel multiscale representation (MSR) for shapes via level set motions and partial differential equations (PDEs). Based on the MSR, we wi...
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
Abstract This paper presents a novel algorithm for performing integrated segmentation and 3D pose estimation of a human body from multiple views. Unlike other state of the art meth...
Pushmeet Kohli, Jonathan Rihan, Matthieu Bray, Phi...