Abstract. We present a novel model for object recognition and detection that follows the widely adopted assumption that objects in images can be represented as a set of loosely cou...
Thomas Deselaers, Andre Hegerath, Daniel Keysers, ...
In this paper we extend a method that uses image patch histograms and discriminative training to recognize objects in cluttered scenes. The method generalizes and performs well for...
We present an approach to the recognition of complexshaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backg...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Abstract—During the last few years a wide range of algorithms and devices have been made available to easily acquire range images. To this extent, the increasing abundance of dep...