We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
We propose in this paper a general kernel framework to deal with database object retrieval embedded in images with heterogeneous background. We use local features computed on fuzz...
Philippe Henri Gosselin, Matthieu Cord, Sylvie Phi...
The goal of our work is object categorization in real-world scenes. That is, given a novel image we want to recognize and localize unseen-before objects based on their similarity t...
Automatic facial feature localization has been a longstanding challenge in the field of computer vision for several decades. This can be explained by the large variation a face i...
Minh Hoai Nguyen, Joan Perez, Fernando De la Torre
This paper presents a parts-based method for classifying scenes of 3D objects into a set of pre-determined object classes. Working at the part level, as opposed to the whole objec...
Daniel F. Huber, Anuj Kapuria, Raghavendra Donamuk...