We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or p...
We present in this paper a system which automatically
builds, from real images, a scene model containing both
3D geometric information of the scene structure and its
photometric...
Most object detection techniques discussed in the literature are based solely on texture-based features that capture the global or local appearance of an object. While results indi...
Recognition systems attempt to recover information about the identity of observed objects and their location in the environment. A fundamental problem in recognition is pose estima...