Name
Abstract | ||
|---|---|---|
This paper presents an approach to the local stereovision matching problem using edge segments as features with four attributes. From these attributes we compute a matching probability between pairs of features of the stereo images. A correspondence is said true when such a probability is maximum. We introduce a nonparametric strategy based on Parzen's window (1962) to estimate a probability density function (PDF) which is used to obtain the matching probability. This is the main finding of the paper. A comparative analysis of other recent matching methods is included to show that this finding can be justified theoretically. A generalization of the proposed method is made in order to give guidelines about its use with the similarity constraint and also in different environments where other features and attributes are more suitable. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/3477.990879 | Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions |
Keywords | Field | DocType |
bayes methods,computer vision,image matching,probability,stereo image processing,local stereovision matching problem,matching probability,nonparametric parzen's window,nonparametric strategy,probability density function,stereo images,comparative analysis,stereo vision,bayesian methods,image analysis,layout,indexing terms,object recognition,image segmentation | Template matching,Computer vision,Pattern recognition,Stereopsis,Image matching,Computer science,Nonparametric statistics,Artificial intelligence,Probability density function,Machine learning,Computer stereo vision | Journal |
Volume | Issue | ISSN |
32 | 2 | 1083-4419 |
Citations | PageRank | References |
6 | 0.51 | 17 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gonzalo Pajares | 1 | 206 | 14.43 |
| Jesús De La Cruz | 2 | 271 | 26.56 |