Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Recursive estimation of 3D motion and surface structure from local affine flow parameters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
1 Author(s)
Calway, A. ; Dept. of Comput. Sci., Bristol Univ., UK

A recursive structure from motion algorithm based on optical flow measurements taken from an image sequence is described. It provides estimates of surface normal in addition to 3D 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 3D parameters using an extended Kalman filter. This also estimates the camera focal length and, so, the 3D 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.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:27 ,  Issue: 4 )