On projection matrices pk → p2, k = 3, ..., 6, and their applications in computer vision

L. Wolf; A. Shashua

On projection matrices p^k → p², k = 3, ..., 6, and their applications in computer vision

L. Wolf^*, A. Shashua

^*Corresponding author for this work

Hebrew University of Jerusalem

Research output: Contribution to conference › Paper › peer-review

35 Scopus citations

Abstract

Projection matrices from projective spaces p³ to p² have long been used in multiple-view geometry to model the perspective projection created by the pin-hole camera. In this work we introduce higher-dimensional mappings p^k → p², k = 4,5,6 for the representation of various applications in which the world we view is no longer rigid. We also describe the multi-view constraints from these new projection matrices and methods for extracting the (non-rigid) structure and motion for each application.

Original language	English
Pages	412-419
Number of pages	8
State	Published - 2001
Externally published	Yes
Event	8th International Conference on Computer Vision - Vancouver, BC, United States Duration: 9 Jul 2001 → 12 Jul 2001

Conference

Conference	8th International Conference on Computer Vision
Country/Territory	United States
City	Vancouver, BC
Period	9/07/01 → 12/07/01

Cite this

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abstract = "Projection matrices from projective spaces p3 to p2 have long been used in multiple-view geometry to model the perspective projection created by the pin-hole camera. In this work we introduce higher-dimensional mappings pk → p2, k = 4,5,6 for the representation of various applications in which the world we view is no longer rigid. We also describe the multi-view constraints from these new projection matrices and methods for extracting the (non-rigid) structure and motion for each application.",

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AB - Projection matrices from projective spaces p3 to p2 have long been used in multiple-view geometry to model the perspective projection created by the pin-hole camera. In this work we introduce higher-dimensional mappings pk → p2, k = 4,5,6 for the representation of various applications in which the world we view is no longer rigid. We also describe the multi-view constraints from these new projection matrices and methods for extracting the (non-rigid) structure and motion for each application.

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T2 - 8th International Conference on Computer Vision

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On projection matrices p^k → p², k = 3, ..., 6, and their applications in computer vision

Abstract

Conference

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