Rigid body segmentation and shape description from dense opticalflow under weak perspective
Weber, J.
Malik, J.
Dept. of Eng., California Inst. of Technol., Pasadena, CA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Feb 1997
Volume: 19,
Issue: 2
On page(s): 139-143
ISSN: 0162-8828
References Cited: 21
CODEN: ITPIDJ
INSPEC Accession Number: 5529625
Digital Object Identifier: 10.1109/34.574794
Current Version Published: 2002-08-06
Abstract
We present an algorithm for identifying and tracking independently
moving rigid objects from optical flow. Some previous attempts at
segmentation via optical flow have focused on finding discontinuities in
the flow field. While discontinuities do indicate a change in scene
depth, they do not in general signal a boundary between two separate
objects. The proposed method uses the fact that each independently
moving object has a unique epipolar constraint associated with its
motion. Thus motion discontinuities based on self-occlusion can be
distinguished from those due to separate objects. The use of epipolar
geometry allows for the determination of individual motion parameters
for each object as well as the recovery of relative depth for each point
on the object. The algorithm assumes an affine camera where perspective
effects are limited to changes in overall scale. No camera calibration
parameters are required. A Kalman filter based approach is used for
tracking motion parameters with time
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