We present a technique to adapt the domain of local features through the matching process to augment their discriminative power. We start with local affine features selected and n...
This paper proposes a formalism for reasoning about distributed object-oriented computations. The formalism is an extension of Milner’s CCS with the notion of local time. It allo...
Hough voting methods efficiently handle the high complexity of multiscale,
category-level object detection in cluttered scenes. The primary weakness
of this approach is however t...
Pradeep Yarlagadda, Antonio Monroy and Bjorn Ommer
We present a discriminative shape-based algorithm for object category localization and recognition. Our method learns object models in a weakly-supervised fashion, without requiri...
Marius Leordeanu, Martial Hebert, Rahul Sukthankar
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...