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Abstract: We show how to automatically acquire similarity-invariant shape representations of objects from noisy image sequences under weak perspective. The proposed method is linear and incremental, requiring no more than pseudo-inverse. It is based on the observation that the trajectories that points on the object form in weak-perspective image sequences are linear combinations of three of the trajectories themselves, and that the coefficients of the linear combinations represent shape in an... (Update)
Context of citations to this paper: More
.... and incremental computation of the matrices Q and B bas from at least three images of the object points is described in [Weinshall and Tomasi, 1992]. 26 C Eliminating translation In this appendix we show that translation can be ignored if we set the centroids of both model and...
.... form is obtained by zeroing its three smallest singular values, and it has been used in various contexts in computer vision (e.g. [14, 32, 34]) Unfortunatey, in the presence of noise, S is not guaranteed (and in fact is unlikely) to be positive, and the above method does...
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BibTeX entry: (Update)
Weinshall, D. and Tomasi, C. (1995). Linear and incremental acquisition of invariant shape models from image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(5):512--517. http://citeseer.ist.psu.edu/weinshall95linear.html More
@article{ weinshall95linear,
author = "Daphna Weinshall and Carlo Tomasi",
title = "Linear and Incremental Acquisition of Invariant Shape Models From Image Sequences",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
volume = "17",
number = "5",
pages = "512-517",
year = "1995",
url = "citeseer.ist.psu.edu/weinshall95linear.html" }
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