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» Probabilistic Modeling and Recognition of 3-D Objects
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3DIM
2007
IEEE
14 years 2 months ago
Range Image Segmentation for Modeling and Object Detection in Urban Scenes
We present fast and accurate segmentation algorithms of range images of urban scenes. The utilization of these algorithms is essential as a pre-processing step for a variety of ta...
Cecilia Chao Chen, Ioannis Stamos
IROS
2009
IEEE
161views Robotics» more  IROS 2009»
14 years 2 months ago
Accurate shape-based 6-DoF pose estimation of single-colored objects
— The problem of accurate 6-DoF pose estimation of 3D objects based on their shape has so far been solved only for specific object geometries. Edge-based recognition and trackin...
Pedram Azad, Tamim Asfour, Rüdiger Dillmann
ICCV
2011
IEEE
12 years 7 months ago
Kinecting the dots: Particle Based Scene Flow from depth sensors
The motion field of a scene can be used for object segmentation and to provide features for classification tasks like action recognition. Scene flow is the full 3D motion fiel...
Simon Hadfield, Richard Bowden
NIPS
2004
13 years 9 months ago
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
Le Lu, Gregory D. Hager, Laurent Younes
IBPRIA
2003
Springer
14 years 29 days ago
Probabilistic Observation Models for Tracking Based on Optical Flow
In this paper, we present two new observation models based on optical flow information to track objects using particle filter algorithms. Although optical flow information enabl...
Manuel J. Lucena, José M. Fuertes, Nicolas ...