Stereo matching, or 3D reconstruction from two or multiple 2D images
of a scene, is one of the most active research areas in computer vision. Due to
its ill-posed nature, stereo matching problem still remains challenging
although many stereo algorithms have been developed. Amongst recent
algorithms, graph-based methods are the most popular because of their
excellent performance. On the other hand, occlusion detection is an important
part in stereo problem. Many heuristics have been presented to handle
occlusions.
In this dissertation, three stereo algorithms are presented. The first one
is a local occlusion detection algorithm, so called the competitive approach.
The objective of this algorithm is to label occlusions in the obtained dense
disparity map without occlusions after matching. This algorithm has two
main steps: first, all matching conflicts are labelled in a dense disparity map
after matching without occlusions; second, occlusions are extracted from
matching conflicts via a maximum-value rule. In this dissertation, an
improved cooperative algorithm is presented to improve the original
cooperative algorithm by using the competitive occlusion detection approach.
This algorithm is implemented on some standard test image pairs to
demonstrate its improvement.
The second part of this dissertation proposes two global stereo
algorithms, named left-right consistency graph cuts (LRC-GC) algorithms, to
solve correspondence problem with occlusions. Our objective of this part is to
design good stereo matchers for accurate correspondence computation
including occlusion labelling. These two algorithms are based on graph cuts
and handle occlusions within the global energy minimization process by
enforcing the left-right matching consistency constraint, which states that
only the non-occluded pixels have correspondences and each pair of
correspondences should have the same disparity value. The two novel
algorithms give unique and symmetric results. We compare them with
another graph-based stereo algorithm, which handles occlusions by enforcing
the uniqueness constraint. Experimental results are reported to demonstrate
the excellent performance of the two novel algorithms and to show that they
outperform the algorithm based on the uniqueness constraint.
In the conclusion part, some limitations of these novel algorithms are
discussed and some directions for further research are suggested.
| Date of Award | 15 Jul 2005 |
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| Original language | English |
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| Awarding Institution | - City University of Hong Kong
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| Supervisor | Shiu Yin Kelvin YUEN (Supervisor) |
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- Computer vision
- Image processing
Graph-based stereo correspondence algorithms and occlusion detection
CHEN, S. (Author). 15 Jul 2005
Student thesis: Master's Thesis