We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifier...
Antonio Torralba, Kevin P. Murphy, William T. Free...
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors a...
Marco Pedersoli, Jordi Gonzàlez, Andrew D. Bagdan...
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...
A large variety of image features has been invented for detection of objects of a known class. We propose a framework to optimize the discrimination-efficiency tradeoff in integra...