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Real-time one-dimensional motion estimation and its application in computer vision

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Abstract

Traditional optical flow methods are designed to generate two-dimensional (2D) motion fields. However in some applications, only the motion field along a predefined line is needed, while the rest of the redundant 2D region (Cong et al., CVPR, 2009) can be ignored. In this paper, we propose a general framework for estimating one-dimensional (1D) motion field using the \(L_1\) norm metric, which can be flexible for adding any constraints depending on the specific intention. Compared with 2D methods in model calculation, which often obtain a local optimal solution, our 1D version has the advantage of real-time global optimization and sub-pixel accuracy with a large displacement capacity. The synthesized experiments have justified the effectiveness of our 1D model. Two vision applications are investigated: (i) for crowd counting, we design a novel unified framework for both line of interest and region of interest counting using our 1D motion model to mosaic the dynamic blobs. Such a framework can adapt to new site without scene-specific learning and overcome overfitting. (ii) For visual odometry, we apply our 1D model to estimate the linear velocity of the robot in real time and obtain a comparable result with the benchmark Encoder. Experiments verified that our proposed model can produce satisfactory results in real time.

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Acknowledgments

This work was supported by NSFC (61375014) and also the Foundation of Chinese Scholarship Council.

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Authors and Affiliations

  1. State Key Laboratory of Robotics, Shenyang Institute of Automation, CAS, Shenyang, China

    Yang Cong & Yandong Tang

  2. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Yang Cong & Shuzhi Sam Ge

  3. Lotus Hill Institute, Ezhou, China

    Yang Cong & Haifeng Gong

  4. Google, Mountain view, USA

    Haifeng Gong

  5. Department of Computer Science, University of Rochester, Rochester, USA

    Jiebo Luo

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  1. Yang Cong
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  2. Haifeng Gong
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Correspondence to Yang Cong.

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Cong, Y., Gong, H., Tang, Y. et al. Real-time one-dimensional motion estimation and its application in computer vision. Machine Vision and Applications 26, 633–648 (2015). https://doi.org/10.1007/s00138-015-0688-8

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