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» Learning Depth from Stereo
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PAMI
2008
174views more  PAMI 2008»
13 years 7 months ago
Multiflash Stereopsis: Depth-Edge-Preserving Stereo with Small Baseline Illumination
Traditional stereo matching algorithms are limited in their ability to produce accurate results near depth discontinuities, due to partial occlusions and violation of smoothness co...
Rogerio Feris, Ramesh Raskar, Longbin Chen, Kar-Ha...
CVPR
1999
IEEE
14 years 9 months ago
A Multi-View Approach to Motion and Stereo
This paper presents a new approach to computing dense depth and motion estimates from multiple images. Rather than computing a single depth or motion map from such a collection, w...
Richard Szeliski
IJCV
1998
153views more  IJCV 1998»
13 years 7 months ago
Rational Filters for Passive Depth from Defocus
A fundamental problem in depth from defocus is the measurement of relative defocus between images. The performance of previously proposed focus operators are inevitably sensitive t...
Masahiro Watanabe, Shree K. Nayar
CVPR
2012
IEEE
11 years 10 months ago
Consistent depth maps recovery from a trinocular video sequence
In this paper, we propose a novel dense depth recovery method for a trinocular video sequence. Specifically, we contribute a novel trinocular stereo matching model, which can eff...
Wenzhuo Yang, Guofeng Zhang, Hujun Bao, Jiwon Kim,...
CRV
2005
IEEE
181views Robotics» more  CRV 2005»
14 years 1 months ago
New Multi-baseline Stereo by Counting Interest Points
This paper proposes a novel method for estimating depth from a long image sequence captured by a moving camera. Our idea for estimating a depth map is very simple; only counting i...
Tomokazu Sato, Naokazu Yokoya