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Real-time video stabilization for fast-moving vehicle cameras

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Abstract

Most previous methods of real-time video stabilization are only effective for low-vibrating frames which are usually captured by in-vehicle camera at the low-speed moving. To overcome their ineffectiveness on high-vibrating frames, this paper presents a real-time video stabilization system for the video sequences captured by a fast-moving in-vehicle camera without additional sensors. The proposed method is composed of four parts: frame-shaking judgment, feature classification, evaluating global motion and rotation angle, and frame compensation. Feature points and their motion vectors are employed for judging whether the current frame is shaking or not, and then a conversion matrix is deduced through the perspective projection for classifying such feature points into background or foreground type. Next, the optical flows of background’s feature points are mapped to polar coordinates for obtaining the representative optical-flow cluster of the background. Finally, such a cluster is utilized to calculate the global motion and rotation angle for compensation followed by the Kalman filtering in order to provide the better video stabilization. Experimental results show that the proposed method has good real-time video stabilization for a vehicle camera moving at various speeds and better stabilization performance than other methods for high-vibrating frames when both real-time processing and acceptable stabilization result are considered.

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Acknowledgment

This work was partly supported by the Ministry of Science and Technology, Taiwan, under grants MOST105-2221-E-346-009, MOST104-2221-E-151-008, and MOST104-2622-E-151-015-CC3. The authors wish to express the appreciation to Mr. Jhih-Bin Guo and Prof. Tong-Yee Lee for their help with the experiments. The authors also gratefully acknowledge the helpful comments and suggestions of reviewers, which have improved the quality and presentation.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, Penghu, Taiwan, Republic of China

    Wu-Chih Hu

  2. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan, Republic of China

    Chao-Ho Chen, Tsong-Yi Chen & Min-Yang Peng

  3. Department of Computer Science and Information Engineering, Shu-Te University, Kaohsiung, Taiwan, Republic of China

    Yi-Jen Su

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  1. Wu-Chih Hu
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  2. Chao-Ho Chen
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Correspondence to Chao-Ho Chen.

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Hu, WC., Chen, CH., Chen, TY. et al. Real-time video stabilization for fast-moving vehicle cameras. Multimed Tools Appl 77, 1237–1260 (2018). https://doi.org/10.1007/s11042-016-4291-4

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  • DOI: https://doi.org/10.1007/s11042-016-4291-4

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