Euclidean Shape and Motion from Multiple Perspective Views by Affine Iterations
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Direct Method for Visual Scene Reconstruction
VSR '95 Proceedings of the IEEE Workshop on Representation of Visual Scenes
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
High resolution surface reconstruction from overlapping multiple-views
Proceedings of the twenty-fifth annual symposium on Computational geometry
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This paper addresses automatic calibration of images, where the main goal is to extract information about objects and relations in the scene based on the information contained in the image itself. The purpose of such calibration is to enable, for example, determination of object coordinates, measurements of distances or areas between objects in the image, etc. The idea of the presented work here is to detect objects in the image whose size is known (e.g. traffic signs in the presented case) and to exploit their relative sizes and positions in the image in order to perform the calibration under some assumptions about possible spatial distribution of the objects (e.g. their positioning on a plane in the presented case). This paper describes related research and the method itself. It also shows and discusses the results and proposes possible extensions.