Capturing 2 ½ D Depth and Texture of Time-Varying Scenes Using Structured Infrared Light

Abstract

In this paper, we describe an approach to simultaneously capture visual appearance and depth of a time-varying scene. Our approach is based on projecting structured infrared (IR) light. Specifically, we project a combination of (a) a static vertical IR stripe pattern, and (b) a horizontal IR laser line sweeping up and down the scene; at the same time, the scene is captured with an IR-sensitive camera. Since IR light is invisible to the human eye, it does not disturb human subjects or interfere with human activities in the scene; in addition, it does not affect the scene’s visual appearance as recorded by a color video camera. Vertical lines in the IR frames are identified using the horizontal line, intra-frame tracking, and inter-frame tracking; depth along these lines is reconstructed via triangulation. Interpolating these sparse depth lines within the foreground silhouette of the recorded video sequence, we obtain a dense depth map for every frame in the video sequence. Experimental results corresponding to a dynamic scene with a human subject in motion are presented to demonstrate the effectiveness of our proposed approach.

Cite

Text

Früh and Zakhor. "Capturing 2 ½ D Depth and Texture of Time-Varying Scenes Using Structured Infrared Light." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005. doi:10.1109/CVPR.2005.428

Markdown

[Früh and Zakhor. "Capturing 2 ½ D Depth and Texture of Time-Varying Scenes Using Structured Infrared Light." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2005.](https://mlanthology.org/cvprw/2005/fruh2005cvprw-capturing/) doi:10.1109/CVPR.2005.428

BibTeX

@inproceedings{fruh2005cvprw-capturing,
  title     = {{Capturing 2 ½ D Depth and Texture of Time-Varying Scenes Using Structured Infrared Light}},
  author    = {Früh, Christian and Zakhor, Avideh},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2005},
  pages     = {102},
  doi       = {10.1109/CVPR.2005.428},
  url       = {https://mlanthology.org/cvprw/2005/fruh2005cvprw-capturing/}
}