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Simultaneous estimation of ego-motion and vehicle distance by using a monocular camera

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Abstract

Auto navigation and vehicle distance estimation are of the critical importance in intelligent vehicles. This paper proposes a novel approach to solve these two problems simultaneously by using a monocular camera. First, we introduce an incremental depth parameterized model to overcome the scale ambiguity problem in monocular vision, which differs from other parameterized models with reduced state-dimension and consistent observability. In addition, the view-field of camera is divided into static and dynamic parts so that the egomotion and vehicle-space can be calculated simultaneously. Outdoor experiments are implemented to validate the effectiveness of the proposed approach.

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Authors and Affiliations

  1. The Second Artillery Engineering University, Xi’an, 710025, China

    DongFang Yang, ShiCheng Wang & JinSheng Zhang

  2. State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, 100084, China

    DongFang Yang & FuChun Sun

Authors
  1. DongFang Yang
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  2. FuChun Sun
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  3. ShiCheng Wang
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  4. JinSheng Zhang
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Correspondence to DongFang Yang.

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Yang, D., Sun, F., Wang, S. et al. Simultaneous estimation of ego-motion and vehicle distance by using a monocular camera. Sci. China Inf. Sci. 57, 1–10 (2014). https://doi.org/10.1007/s11432-013-4884-8

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  • DOI: https://doi.org/10.1007/s11432-013-4884-8

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