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 ...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
We present a novel approach for multi-object tracking which considers object detection and spacetime trajectory estimation as a coupled optimization problem. It is formulated in a...
We formulate multi-view 3D shape reconstruction as the computation of a minimum cut on the dual graph of a semiregular, multi-resolution, tetrahedral mesh. Our method does not ass...
Sudipta N. Sinha, Philippos Mordohai, Marc Pollefe...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...