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ECCV
2010
Springer
13 years 8 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang
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
AAAI
1993
13 years 9 months ago
Learning Object Models from Appearance
We address the problem of automatically learning object models for recognition and pose estimation. In contrast to the traditional approach, we formulate the recognition problem a...
Hiroshi Murase, Shree K. Nayar
PAMI
2002
112views more  PAMI 2002»
13 years 7 months ago
Feature Space Trajectory Methods for Active Computer Vision
We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or p...
Michael A. Sipe, David Casasent
IVC
2010
95views more  IVC 2010»
13 years 6 months ago
Monocular head pose estimation using generalized adaptive view-based appearance model
Accurately estimating the person’s head position and orientation is an important task for a wide range of applications such as driver awareness, meeting analysis and human-robot...
Louis-Philippe Morency, Jacob Whitehill, Javier R....