Inferring both 3D structure and motion of nonrigid objects from monocular images is an important problem in computational vision. The challenges stem not only from the absence of ...
Our paper has two main contributions. Firstly, it presents a model for image sequences motivated by an image encoding perspective. It models accreted regions, where objects appear...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Image artifacts that result from sensor dust are a common but annoying problem for many photographers. To reduce the appearance of dust in an image, we first formulate a model of ...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...