3D object recognition in scenes with occlusion and clutter is a difficult task. In this paper, we introduce a method that exploits the geometric scale-variability to aid in this ...
Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
We consider the problem of extracting features for multi-class recognition problems. The features are required to make fine distinction between similar classes, combined with tole...
This paper deals with a new interest points detector. Unlike most standard detectors which concentrate on the local shape of the signal, the main objective of this new operator is...