In this paper, we study the problem of fine-grained image categorization. The goal of our method is to explore fine image statistics and identify the discriminative image patche...
We propose a dense local region detector to extract features suitable for image matching and object recognition tasks. Whereas traditional local interest operators rely on repeata...
Color is known to be highly discriminative for many object recognition tasks, but is difficult to infer from uncontrolled images in which the illuminant is not known. Traditional...
Trevor Owens, Kate Saenko, Trevor Darrell, Ayan Ch...
This paper extends classical object pose and relative camera motion estimation algorithms for imaging sensors sampling the scene through light-paths. Many algorithms in multi-view...
Srikumar Ramalingam, Sofien Bouaziz, Peter Sturm, ...
We present a new paradigm for tracking objects in video in the presence of other similar objects. This branch-andtrack paradigm is also useful in the absence of motion, for the di...