Online boosting is one of the most successful online learning algorithms in computer vision. While many challenging online learning problems are inherently multi-class, online boo...
Amir Saffari, Martin Godec, Thomas Pock, Christian...
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
A new learning strategy for object detection is presented.
The proposed scheme forgoes the need to train a collection
of detectors dedicated to homogeneous families of poses,
an...
Karim Ali, Francois Fleuret, David Hasler and Pasc...
Human-area segmentation is a major issue in video surveillance. Many existing methods estimate individual human areas from the foreground area obtained by background subtraction, ...
We propose a novel general framework with a boosting algorithm to achieve active object classification by view selection. The proposed framework actively decides the next best vie...