We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
This work addresses the important problem of the discovery
and analysis of social networks from surveillance video.
A computer vision approach to this problem is made possible
b...
Ting Yu, Ser Nam Lim, Kedar A. Patwardhan, Nils Kr...
Most modern computer vision systems for high-level
tasks, such as image classification, object recognition and
segmentation, are based on learning algorithms that are
able to se...
The state-of-the art in visual object retrieval from large
databases allows to search millions of images on the object
level. Recently, complementary works have proposed systems
...
Stephan Gammeter, Lukas Bossard, Till Quack, Luc V...
We propose a novel framework for contour based object
detection and recognition, which we formulate as a joint
contour fragment grouping and labeling problem. For a
given set of...
ChengEn Lu, Longin Jan Latecki, Nagesh Adluru, Hai...