Bi-directional Shape Correspondences (BSC)
We propose Bidirectional Shape Correspondence (BSC) as a possible improvement on the famous shape contexts (SC) framework. Our proposals derive from the observation that the SC framework enforces a one-to-one correspondence between sample points, and that this leads to two possible drawbacks. First,...
में बचाया:
| मुख्य लेखक: | |
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| स्वरूप: | Conference paper |
| भाषा: | Spanish / Castilian |
| प्रकाशित: |
Abdulrahman Ibraheem
2023
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| विषय: | |
| ऑनलाइन पहुंच: | https://ir.oauife.edu.ng/123456789/5607 |
| टैग: |
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| सारांश: | We propose Bidirectional Shape Correspondence (BSC) as a possible improvement on the famous shape contexts (SC) framework. Our proposals derive from the observation that the SC framework enforces a one-to-one correspondence between sample points, and that this leads to two possible drawbacks. First, this denies the framework the opportunity to effect advantageous many-to-many matching between points on the two shapes being compared. Second, this calls for the Hungarian algorithm which unfortunately usurps cubic time. While the dynamic-space-warping dynamic programming algorithm has provided a standard solution to the first problem above, it demands quintic time for general multi-contour shapes, and w times quadratic time for the special case of single-contour shapes, even after an heuristic search window of width w has been chosen. Therefore, in this work, we propose a simple method for computing "many-to-many" correspondences for the class of all 2-d shapes in quadratic time. Our approach is to explicitly let each point on the first shape choose a best match on the second shape, and vice versa. Along the way, we also propose the use of data-clustering techniques for dealing with the outliers problem, and, from another viewpoint, it turns out that this clustering can be seen as an autonomous, rather than pre-computed, sampling of shape boundary. |
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