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» Probabilistic Modeling and Recognition of 3-D Objects
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MVA
1990
162views Computer Vision» more  MVA 1990»
13 years 9 months ago
Map-Driven Image Interpretation by Associative Model Indexing
d at a high abstraction level, and consists in an expectation-driven search starting from symbolic object descriptions and using a version of a distributed blackboard system for re...
Gian Luca Foresti, Vittorio Murino, Carlo S. Regaz...
DICTA
2008
13 years 9 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...
AAAI
2012
11 years 10 months ago
Model Learning and Real-Time Tracking Using Multi-Resolution Surfel Maps
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
Jörg Stückler, Sven Behnke
CVIU
2004
143views more  CVIU 2004»
13 years 7 months ago
Shape matching of partially occluded curves invariant under projective transformation
This paper describes a method to identify partially occluded shapes which are randomly oriented in 3D space. The goal is to match the object contour present in an image with an ob...
Carlos Orrite, José Elías Herrero Ja...
AMFG
2003
IEEE
126views Biometrics» more  AMFG 2003»
14 years 1 months ago
Rank Constrained Recognition under Unknown Illuminations
Recognition under illumination variations is a challenging problem. The key is to successfully separate the illumination source from the observed appearance. Once separated, what ...
Shaohua Kevin Zhou, Rama Chellappa