This paper presents a novel people detection and tracking method based on a multi-modal sensor fusion approach that utilizes 2D laser range and camera data. The data points in the...
Luciano Spinello, Rudolph Triebel, Roland Siegwart
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Accurately and automatically conveying the structure of a volume model is a problem not fully solved by existing volume rendering approaches. Physics-based volume rendering approa...
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
In deformable model segmentation, the geometric training process plays a crucial role in providing shape statistical priors and appearance statistics that are used as likelihoods. ...
Qiong Han, Derek Merck, Josh Levy, Christina Villa...