Journal ArticleDOI
Obtaining depth map from segment-based stereo matching using graph cuts
Daolei Wang,Kah Bin Lim +1 more
TLDR
The algorithm of segment-based stereo matching using graph cuts is developed for extracting depth information from the stereo image pairs by employing the mean-shift algorithm and the use of Adaptive Support Weighted Self-Adaptation dissimilarity algorithm for the estimation of initial disparity.About:
This article is published in Journal of Visual Communication and Image Representation.The article was published on 2011-05-01. It has received 42 citations till now. The article focuses on the topics: Depth map & Cut.read more
Citations
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Journal ArticleDOI
Optimal seamline detection for multiple image mosaicking via graph cuts
TL;DR: Experimental results on a large set of aerial, oblique and street-view panoramic images show that the proposed algorithm is capable of creating high-quality seamlines for multiple image mosaicking, while not crossing majority of visually obvious foreground objects and most of overlap regions with low image similarity.
Journal ArticleDOI
Efficient Disparity Estimation Using Hierarchical Bilateral Disparity Structure Based Graph Cut Algorithm With a Foreground Boundary Refinement Mechanism
TL;DR: A hierarchical bilateral disparity structure (HBDS) algorithm in which the efficiency of the GC method is improved without any loss in the disparity estimation performance by dividing all the disparity levels within the stereo image hierarchically into a series of bilateral disparity structures of increasing fineness is proposed.
Journal ArticleDOI
3D entity-based stereo matching with ground control points and joint second-order smoothness prior
TL;DR: A stereo framework that views the scene as a set of 3D entities with compact and smooth disparity distributions with a joint second-order smoothness prior, which combines a geometric weight with the derivative of disparity values to encourage smooth disparity variations inside each entity.
Journal ArticleDOI
Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach
TL;DR: A segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps and the experimental results with the Middlebury stereo datasets, along with synthesized and real-world stereo images, demonstrate the effectiveness of the proposed approach.
Journal ArticleDOI
A Survey on Stereo Matching Techniques for 3D Vision in Image Processing
Deepika Kumari,Kamaljit Kaur +1 more
TL;DR: A review on various stereo matching techniques has shown that the existing methods in stereo matching involve median filtering, but median filter is not effective for high density of noise.
References
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Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
Fast approximate energy minimization via graph cuts
TL;DR: This work presents two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves that allow important cases of discontinuity preserving energies.
Journal ArticleDOI
What energy functions can be minimized via graph cuts
Vladimir Kolmogorov,R. Zabin +1 more
TL;DR: This work gives a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables.
Journal ArticleDOI
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.