Abstract. The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range ...
Local appearance models in the neighborhood of salient image features, together with local and/or global geometric constraints, serve as the basis for several recent and effective...
We describe a method for implementing the evaluation and training of decision trees and forests entirely on a GPU, and show how this method can be used in the context of object rec...
Abstract. An important task in object recognition is to enable algorithms to categorize objects under arbitrary poses in a cluttered 3D world. A recent paper by Savarese & Fei-...
A novel approach to grouping symmetrical planar curves under a projective transform is described. Symmetric curves are important as a generic model for object recognition where an...
Rupert W. Curwen, Charles V. Stewart, Joseph L. Mu...
While navigating in an environment, a vision system has to be able to recognize where it is and what the main objects in the scene are. In this paper we present a contextbased vis...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
Previous studies have demonstrated that the appearance of an object under varying illumination conditions can be represented by a low-dimensional linear subspace. A set of basis i...
This paper presents a probabilistic part-based approach for texture and object recognition. Textures are represented using a part dictionary found by quantizing the appearance of ...
The Internet contains billions of images, freely available online. Methods for efficiently searching this incredibly rich resource are vital for a large number of applications. Th...
Symmetry is one of the important cues for human and machine perception of the world. For over three decades, automatic symmetry detection from images/patterns has been a standing ...
Minwoo Park, Seungkyu Lee, Po-Chun Chen, Somesh Ka...