— In this paper we propose a method of high-speed 3D object recognition using linear subspace method and our 3D features. This method can be applied to partial models with any si...
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
In this paper, we introduce a novel probabilistic approach to handle occlusions and perspective effects. The proposed method is an object based method embedded in a marked point p...
Ahmed Gamal-Eldin, Xavier Descombes, Josiane Zerub...
We present a method that is capable of tracking and estimating pose of articulated objects in real-time. This is achieved by using a bottom-up approach to detect instances of the ...
A probabilistic system for recognition of individual objects is presented. The objects to recognize are composed of constellations of features, and features from a same object shar...