Estimating 3D vehicle motion in an outdoor scene from monocular and stereo image sequences

Mun K. Leung, Yuncai Liu, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The main goal of this research is to test how well existing feature extraction, matching and motion estimation algorithms (with appropriate modification) work on outdoor scenes. For this purpose, a careful calibrated image sequence data base has been created. The data used for the results reported in this paper consists of a sequence of 24 stereo images of an outdoor scene containing a moving truck with stationary background. Two motion estimation methods using feature correspondences were applied in the data: point correspondences over two stereo image pairs and line correspondences over three monocular images. In spite of the large values of the range to baseline ration (10:1) and the range to focal length ration (1000:1), the estimated rotation parameters are reasonably accurate (10-20% errors) in both methods. Although the translation estimates in the monocular method are large, the translation errors in the stereo method are around 1 meter, and are mainly due to image sampling.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Workshop on Visual Motion
PublisherPubl by IEEE
Pages62-68
Number of pages7
ISBN (Print)0818621532
StatePublished - 1991
EventProceedings of the IEEE Workshop on Visual Motion - Princeton, NJ, USA
Duration: Oct 7 1991Oct 9 1991

Publication series

NameProceedings of the IEEE Workshop on Visual Motion

Other

OtherProceedings of the IEEE Workshop on Visual Motion
CityPrinceton, NJ, USA
Period10/7/9110/9/91

ASJC Scopus subject areas

  • Engineering(all)

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