Title :
Affine reconstruction of curved surfaces from uncalibrated views of apparent contours
Author :
Sato, Jun ; Cipolla, Roberto
Author_Institution :
Dept. of Electr. & Comput. Eng., Nagoya Inst. of Technol., Japan
fDate :
11/1/1999 12:00:00 AM
Abstract :
In this paper, we consider uncalibrated reconstruction of curved surfaces from apparent contours. Since apparent contours are not fixed features (viewpoint independent), we cannot directly apply the recent results of the uncalibrated reconstruction from fixed features. We show that, nonetheless, curved surfaces can be reconstructed up to an affine ambiguity from their apparent contours viewed from uncalibrated cameras with unknown linear translations. Furthermore, we show that, even if the reconstruction is nonmetric (non-Euclidean), we can still extract useful information for many computer vision applications just from the apparent contours. We first show that if the camera motion is linear translation (but arbitrary direction and magnitude), the epipolar geometry can be recovered from the apparent contours without using any optimization process. The extracted epipolar geometry is next used for reconstructing curved surfaces from the deformations of the apparent contours viewed from uncalibrated cameras. The result is applied to distinguishing curved surfaces from fixed features in images. It is also shown that the time-to-contact to the curved surfaces can be computed from simple measurements of the apparent contours
Keywords :
computer vision; image reconstruction; affine ambiguity; affine reconstruction; apparent contour deformation; curved surfaces; epipolar geometry; linear translation; non-Euclidean reconstruction; nonEuclidean reconstruction; nonmetric reconstruction; uncalibrated cameras; uncalibrated views; unknown linear translations; Application software; Cameras; Computational geometry; Computer vision; Data mining; Image reconstruction; Information geometry; Motion estimation; Notice of Violation; Surface reconstruction;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on