Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
Abstract. Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model i...
Vikas Reddy, Conrad Sanderson, Andres Sanin, Brian...
We present a discriminative Hough transform based ob-
ject detector where each local part casts a weighted vote for
the possible locations of the object center. We show that the
...
Subhransu Maji (University of California, Berkeley...
We propose a new approach for detecting low textured
planar objects and estimating their 3D pose. Standard
matching and pose estimation techniques often depend on
texture and fe...
Stefan Holzer, Stefan Hinterstoisser, Slobodan Ili...
Detecting regions of interest in video sequences is the most important task in many high level video processing applications. In this paper a robust technique based on recursive l...