Recursive Estimation of 3-D Motion and Surface Structure from Local Affine Flow Parameters

Research output: Contribution to journalArticle (Academic Journal)

20 Citations (Scopus)

Abstract

A recursive structure from motion algorithm based on optical flow measurements taken from an image sequence is described. It provides estimates of surface normals in addition to 3-D motion and depth. The measurements are affine motion parameters which approximate the local flow fields associated with near-planar surface patches in the scene. These are integrated over time to give estimates of the 3-D parameters using an extended Kalman filter. This also estimates the camera focal length and hence the 3-D estimates are metric. The use of parametric measurements means that the algorithm is computationally less demanding than previous optical flow approaches and the recursive filter builds in a degree of noise robustness. Results of experiments on synthetic and real image sequences demonstrate that the algorithm performs well.
Translated title of the contributionRecursive Estimation of 3-D Motion and Surface Structure from Local Affine Flow Parameters
Original languageEnglish
Pages (from-to)562 - 574
Number of pages13
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume27 (4)
DOIs
Publication statusPublished - Apr 2005

Bibliographical note

Publisher: Institute of Electrical and Electronic Engineers
Other: http://www.cs.bris.ac.uk/Publications/pub_info.jsp?id=2000211

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