We develop a method that can detect humans in a single image based on a new cascaded structure. In our approach, both the rectangle features and 1-D edge-orientation features are e...
The co-occurrence pattern, a combination of binary or local features, is more discriminative than individual features and has shown its advantages in object, scene, and action rec...
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
We consider the problem of detecting a large number of different object classes in cluttered scenes. Traditional approaches require applying a battery of different classifiers to ...
Antonio B. Torralba, Kevin P. Murphy, William T. F...