Conventional stereo matching algorithms assume color constancy on the corresponding opaque pixels in the stereo images. However, when the foreground objects with fractional bounda...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
The observation models in tracking algorithms are critical to both tracking performance and applicable scenarios but are often simplified to focus on fixed level of certain target...
The objective of this work is automatic detection and identification of individuals in unconstrained consumer video, given a minimal number of labelled faces as training data. Whi...