Comparer des méthodes

	Correspondance stéréoscopique	Correspondance de modèle
Domaine	Vision par ordinateur	Vision par ordinateur
Famille	Machine learning	Machine learning
Année d'origine	1990s	1980s
Auteur d'origine	David Scharstein and Richard Szeliski	Computer vision community
Type	Depth estimation and 3D vision	Pattern matching and detection
Source fondatrice	Scharstein, D., & Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1), 7–42.	Lewis, J. P. (2004). Fast normalized cross-correlation. Vision Interface, 120–123.
Alias	Stereo correspondence, Disparity estimation	Correlation-based matching, Similarity matching
Apparentées	5	5
Résumé	Stereo matching is a computer vision technique for recovering depth information by finding corresponding points between a pair of stereo images (taken from slightly different viewpoints). By locating the same scene feature in both images and measuring the disparity (horizontal shift), stereo matching reconstructs 3D structure using the principles of triangulation.	Template matching is a straightforward technique for locating a known pattern (template) within a larger image. By sliding a template image across the target image and computing a similarity measure at each position, template matching identifies locations where the template appears. It is effective for simple object detection when templates are well-defined and appearance variation is limited.