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Superpixel-based color–depth restoration and dynamic environment modeling for Kinect-assisted image-based rendering systems

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Abstract

Depth information is an important ingredient in many multiview applications including image-based rendering (IBR). With the advent of electronics, low-cost and high-speed depth cameras, such as the Microsoft Kinect, are getting increasingly popular. In this paper, we propose a superpixel-based joint color–depth restoration approach for Kinect depth camera and study its application to view synthesis in IBR systems. Thus, an edge-based matching method is proposed to reduce the color–depth registration errors. Then the Kinect depth map is restored based on probabilistic color–depth superpixels, probabilistic local polynomial regression and joint color–depth matting. The proposed restoration algorithm does not only inpaint the missing data, but also correct and refine the depth map to provide better color–depth consistency. Last but not the least, a dynamic background modeling scheme is proposed to address the disocclusion problem in the view synthesis for dynamic environment. The experimental results show the effectiveness of the proposed algorithm and system.

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Author information

Correspondence to Chong Wang.

Additional information

This work was supported in part by K.C. Wong Magna Fund in Ningbo University; National Natural Science Foundation of China (61603202); Zhejiang Open Foundation from Information and Communication Engineering of the Most Important Subjects, China (xkxl1512, xkxl1526); the Open Project Program of the State Key Lab of CAD\( { \& }\)CG in Zhejiang University (A1606); the Research Foundation of Education Department of Zhejiang Province, China (Y201533827); Zhejiang Provincial Natural Science Foundation, China (LQ16F030001); Ningbo Natural Science Foundation, China (2016A610070) and the General Research Fund (GRF) of Hong Kong Research Grant Council (RGC).

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Wang, C., Chan, S., Zhu, Z. et al. Superpixel-based color–depth restoration and dynamic environment modeling for Kinect-assisted image-based rendering systems. Vis Comput 34, 67–81 (2018). https://doi.org/10.1007/s00371-016-1312-2

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Keywords

  • Image-based rendering
  • Superpixel
  • Kinect
  • Background modeling
  • Local polynomial regression