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Self-Motion and Depth Estimation from Image SequencesAn image-based version of a computational model of human self-motion perception (developed in collaboration with Dr. Leland S. Stone at NASA Ames Research Center) has been generated and tested. The research included in the grant proposal sought to extend the utility of the self-motion model so that it could be used for explaining and predicting human performance in a greater variety of aerospace applications. The model can now be tested with video input sequences (including computer generated imagery) which enables simulation of human self-motion estimation in a variety of applied settings.
Document ID
20000021023
Acquisition Source
Ames Research Center
Document Type
Contractor or Grantee Report
Authors
Perrone, John
(Waikato Univ. Hamilton, New Zealand)
Date Acquired
August 19, 2013
Publication Date
July 2, 1999
Subject Category
Man/System Technology And Life Support
Funding Number(s)
CONTRACT_GRANT: NAG2-1168
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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