Intensity- and gradient-based stereo matching using hierarchical Gaussian basis functions
| Autor: | G. Hirzinger, W. Brauer, Guo-Qing Wei |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
business.industry
Estimation theory Applied Mathematics Gaussian ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Stereo matching Basis function Scale space Maxima and minima symbols.namesake Computational Theory and Mathematics Artificial Intelligence Computer Science::Computer Vision and Pattern Recognition symbols Computer vision Computer Vision and Pattern Recognition Artificial intelligence Uniqueness Minification business Algorithm Software Mathematics |
| Zdroj: | IEEE Transactions on Pattern Analysis and Machine Intelligence. 20:1143-1160 |
| ISSN: | 0162-8828 |
| DOI: | 10.1109/34.730551 |
| Popis: | We propose a stereo correspondence method by minimizing intensity and gradient errors simultaneously. In contrast to conventional use of image gradients, the gradients are applied in the deformed image space. Although a uniform smoothness constraint is imposed, it is applied only to nonfeature regions. To avoid local minima in the function minimization, we propose to parameterize the disparity function by hierarchical Gaussians. Both the uniqueness and the ordering constraints can be easily imposed in our minimization framework. Besides, we propose a method to estimate the disparity map and the camera response difference parameters simultaneously. Experiments with various real stereo images show robust performances of our algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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