Comparison of point and line features and their combination for rigid body motion estimation

Pilz, F., Pugeault, N. and Krüger, N. (2009) Comparison of point and line features and their combination for rigid body motion estimation. In: Cremers, D., Rosenhahn, B., Yuille, A. L. and Schmidt, F. R. (eds.) Statistical and Geometrical Approaches to Visual Motion Analysis: International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008. Revised Papers. Series: Lecture notes in computer science (5604). Springer: Berlin ; New York, pp. 280-304. ISBN 9783642030604 (doi: 10.1007/978-3-642-03061-1_14)

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Abstract

This paper discusses the usage of different image features and their combination in the context of estimating the motion of rigid bodies (RBM estimation). From stereo image sequences, we extract line features at local edges (coded in so called multi-modal primitives) as well as point features (by means of SIFT descriptors). All features are then matched across stereo and time, and we use these correspondences to estimate the RBM by solving the 3D-2D pose estimation problem. We test different feature sets on various stereo image sequences, recorded in realistic outdoor and indoor scenes. We evaluate and compare the results using line and point features as 3D-2D constraints and we discuss the qualitative advantages and disadvantages of both feature types for RBM estimation. We also demonstrate an improvement in robustness through the combination of these features on large data sets in the driver assistance and robotics domain. In particular, we report total failures of motion estimation based on only one type of feature on relevant data sets.

Item Type:Book Sections
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Pugeault, Dr Nicolas
Authors: Pilz, F., Pugeault, N., and Krüger, N.
College/School:College of Science and Engineering > School of Computing Science
Publisher:Springer
ISBN:9783642030604

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