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» Optimal Parameter Estimation for MRF Stereo Matching
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IJCV
2000
225views more  IJCV 2000»
13 years 7 months ago
Depth from Defocus vs. Stereo: How Different Really Are They?
Depth from Focus (DFF) and Depth from Defocus (DFD) methods are theoretically unified with the geometric triangulation principle. Fundamentally, the depth sensitivities of DFF and ...
Yoav Y. Schechner, Nahum Kiryati
PAMI
1998
94views more  PAMI 1998»
13 years 7 months ago
Unconstrained Automatic Image Matching Using Multiresolutional Critical-Point Filters
—This paper proposes a novel method for matching images. The results can be used for a variety of applications: fully automatic morphing, object recognition, stereo photogrammetr...
Yoshihisa Shinagawa, Tosiyasu L. Kunii
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,...
ECCV
2008
Springer
14 years 9 months ago
A Segmentation Based Variational Model for Accurate Optical Flow Estimation
Segmentation has gained in popularity in stereo matching. However, it is not trivial to incorporate it in optical flow estimation due to the possible non-rigid motion problem. In t...
Li Xu, Jianing Chen, Jiaya Jia
ISVC
2009
Springer
14 years 2 months ago
Real-Time Feature Acquisition and Integration for Vision-Based Mobile Robots
In this paper we propose a new system for real-time feature acquisition and integration based on high-resolution stereo images that is suitable for mobile robot platforms with limi...
Thomas Hübner, Renato Pajarola