Multi-Spectral Visual Odometry without Explicit Stereo Matching

Weichen Dai, Yu Zhang, Donglei Sun, Naira Hovakimyan, Ping Li

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

Abstract

Multi-spectral sensors consisting of a standard (visible-light) camera and a long-wave infrared camera can simultaneously provide both visible and thermal images. Since thermal images are independent from environmental illumination, they can help to overcome certain limitations of standard cameras under complicated illumination conditions. However, due to the difference in the information source of the two types of cameras, their images usually share very low texture similarity. Hence, traditional texture-based feature matching methods cannot be directly applied to obtain stereo correspondences. To tackle this problem, a multi-spectral visual odometry method without explicit stereo matching is proposed in this paper. Bundle adjustment of multi-view stereo is performed on the visible and the thermal images using direct image alignment. Scale drift can be avoided by additional temporal observations of map points with the fixed-baseline stereo. Experimental results indicate that the proposed method can provide accurate visual odometry results with recovered metric scale. Moreover, the proposed method can also provide a metric 3D reconstruction in semi-dense density with multi-spectral information, which is not available from existing multi-spectral methods.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 International Conference on 3D Vision, 3DV 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages443-452
Number of pages10
ISBN (Electronic)9781728131313
DOIs
StatePublished - Sep 2019
Event7th International Conference on 3D Vision, 3DV 2019 - Quebec, Canada
Duration: Sep 15 2019Sep 18 2019

Publication series

NameProceedings - 2019 International Conference on 3D Vision, 3DV 2019

Conference

Conference7th International Conference on 3D Vision, 3DV 2019
CountryCanada
CityQuebec
Period9/15/199/18/19

Keywords

  • Egomotion estimation
  • Multi spectral sensors
  • Visual Odometry

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Media Technology
  • Modeling and Simulation

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  • Cite this

    Dai, W., Zhang, Y., Sun, D., Hovakimyan, N., & Li, P. (2019). Multi-Spectral Visual Odometry without Explicit Stereo Matching. In Proceedings - 2019 International Conference on 3D Vision, 3DV 2019 (pp. 443-452). [8885483] (Proceedings - 2019 International Conference on 3D Vision, 3DV 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/3DV.2019.00056