Proceedings Article10.1109/CVPRW.2010.5543769
A census-based stereo vision algorithm using modified Semi-Global Matching and plane fitting to improve matching quality
Martin Humenberger,Tobias Engelke,Wilfried Kubinger +2 more
- 13 Jun 2010
- pp 77-84
TL;DR: A new segmentation-based approach for disparity optimization in stereo vision by segmenting either the left color image or the calculated texture image and it is shown that this modification significantly reduces the memory consumption by nearly constant matching quality and thus enables embedded realization.
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Abstract: This paper introduces a new segmentation-based approach for disparity optimization in stereo vision. The main contribution is a significant enhancement of the matching quality at occlusions and textureless areas by segmenting either the left color image or the calculated texture image. The local cost calculation is done with a Census-based correlation method and is compared with standard sum of absolute differences. The confidence of a match is measured and only non-confident or non-textured pixels are estimated by calculating a disparity plane for the corresponding segment. The quality of the local optimized matches is increased by a modified Semi-Global Matching (SGM) step with subpixel accuracy. In contrast to standard SGM, not the whole image is used for disparity optimization but horizontal stripes of the image. It is shown that this modification significantly reduces the memory consumption by nearly constant matching quality and thus enables embedded realization. Using the Middlebury ranking as evaluation criterion, it is shown that the proposed algorithm performs well in comparison to the pure Census correlation. It reaches a top ten rank if subpixel accuracy is supposed. Furthermore, the matching quality of the algorithm, especially of the texture-based plane fitting, is shown on two real-world scenes where a significant enhancement could be achieved.
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Review of stereo vision algorithms and their suitability for resource-limited systems
TL;DR: This work provides a comprehensive review of stereo vision algorithms with specific emphasis on real-time performance to identify those suitable for resource-limited systems and to encourage further research and development of the same.
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Large scale Semi-Global Matching on the CPU
Robert Spangenberg,Tobias Langner,Sven Adfeldt,Raúl Rojas +3 more
- 08 Jun 2014
TL;DR: Methods to improve the efficiency of SGM on general purpose PCs, through fine grained parallelization and usage of multiple cores are studied, which are scalable to the number of available cores and portable to embedded processors.
Left-Right Comparative Recurrent Model for Stereo Matching
Zequn Jie,Pengfei Wang,Ling Yonggen,Bo Zhao,Yunchao Wei,Jiashi Feng,Wei Liu +6 more
- 01 Jun 2018
TL;DR: Zhang et al. as mentioned in this paper proposed a left-right comparative recurrent model to perform leftright consistency checking jointly with disparity estimation, which leverages the disparity information from both left and right views.
Stereo matching algorithm based on per pixel difference adjustment, iterative guided filter and graph segmentation
TL;DR: The proposed algorithm utilizes per-pixel difference adjustment for AD and gradient matching to reduce the radiometric distortions and a new approach of iterative guided filter is introduced at cost aggregation to preserve and improve the object boundaries.
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Enhanced disparity estimation in stereo images
TL;DR: A novel stereo disparity estimation method, which combines three different cost metrics, defined using RGB information, the CENSUS transform, as well as Scale-Invariant Feature Transform coefficients, which ranks first among published methods in the Middlebury evaluation system.
47
References
Mean shift: a robust approach toward feature space analysis
Dorin Comaniciu,Peter Meer +1 more
TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
12.9K
A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.
Non-parametric local transforms for computing visual correspondence
Ramin Zabih,John Iselin Woodfill +1 more
- 07 May 1994
TL;DR: A new approach to the correspondence problem that makes use of non-parametric local transforms as the basis for correlation, which can result in improved performance near object boundaries when compared with conventional methods such as normalized correlation.
•Book
Understanding belief propagation and its generalizations
Jonathan S. Yedidia,William T. Freeman,Yair Weiss +2 more
- 01 Jan 2003
TL;DR: It is shown that BP can only converge to a fixed point that is also a stationary point of the Bethe approximation to the free energy, which enables connections to be made with variational approaches to approximate inference.
1.8K
Efficient Belief Propagation for Early Vision
TL;DR: Algorithmic techniques are presented that substantially improve the running time of the loopy belief propagation approach and reduce the complexity of the inference algorithm to be linear rather than quadratic in the number of possible labels for each pixel, which is important for problems such as image restoration that have a large label set.
1.6K