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ICCV
2005
IEEE
13 years 10 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
WACV
2005
IEEE
13 years 10 months ago
Shared Features for Scalable Appearance-Based Object Recognition
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
Erik Murphy-Chutorian, Jochen Triesch
DICTA
2008
13 years 6 months ago
Exploiting Part-Based Models and Edge Boundaries for Object Detection
This paper explores how to exploit shape information to perform object class recognition. We use a sparse partbased model to describe object categories defined by shape. The spars...
Josephine Sullivan, Oscar M. Danielsson, Stefan Ca...
CVPR
2010
IEEE
13 years 9 months ago
Model Globally, Match Locally: Efficient and Robust 3D Object Recognition
This paper addresses the problem of recognizing freeform 3D objects in point clouds. Compared to traditional approaches based on point descriptors, which depend on local informati...
Bertram Drost, Markus Ulrich, Nassir Navab, Slobod...
CORR
2011
Springer
211views Education» more  CORR 2011»
12 years 8 months ago
Labeling 3D scenes for Personal Assistant Robots
—Inexpensive RGB-D cameras that give an RGB image together with depth data have become widely available. We use this data to build 3D point clouds of a full scene. In this paper,...
Hema Swetha Koppula, Abhishek Anand, Thorsten Joac...