We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...
Most of the work on 3-D object recognition from range data has used an alignment-verification approach in which a specific 3-D object is matched to an exact instance of the same o...
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Mei...
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
Content understanding is a crucial issue for website adaptation. In this paper we present a Function-based Object Model (FOM) that attempts to understand authors' intention b...
Jinlin Chen, Baoyao Zhou, Jin Shi, HongJiang Zhang...