We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled f...
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...
This paper presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transforms for...
Minh-Tri Pham, Oliver J. Woodford, Frank Perbet, A...
In interest point based human action recognition, local descriptors are used to represent information in the neighbourhood around each extracted space-time interest point. The per...
This paper presents a unified framework for object detection,
segmentation, and classification using regions. Region
features are appealing in this context because: (1) they enco...
Chunhui Gu, Joseph J. Lim, Pablo Arbelaez, Jitendr...