In this paper we propose a robust method for recognition and pose determination of 3-D objects using range images in the eigenspace approach. Instead of computing the coefficients...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
Dmitry N. Zotkin, Ramani Duraiswami, Larry S. Davi...
Polygonal models are the most common representation of structured 3D data in computer graphics, pattern recognition and machine vision. The method presented here automatically ide...
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...