International Journal of Computer Vision

, Volume 110, Issue 2, pp 141–155

Acquisition of High Spatial and Spectral Resolution Video with a Hybrid Camera System

  • Chenguang Ma
  • Xun Cao
  • Xin Tong
  • Qionghai Dai
  • Stephen Lin
Article

DOI: 10.1007/s11263-013-0690-4

Cite this article as:
Ma, C., Cao, X., Tong, X. et al. Int J Comput Vis (2014) 110: 141. doi:10.1007/s11263-013-0690-4

Abstract

We present a hybrid camera system for capturing video at high spatial and spectral resolutions. Composed of an red, green, and blue (RGB) video camera, a grayscale video camera and a few optical elements, the hybrid camera system simultaneously records two video streams: an RGB video with high spatial resolution, and a multispectral (MS) video with low spatial resolution. After registration of the two video streams, our system propagates the MS information into the RGB video to produce a video with both high spectral and spatial resolution. This propagation between videos is guided by color similarity of pixels in the spectral domain, proximity in the spatial domain, and the consistent color of each scene point in the temporal domain. The propagation algorithm, based on trilateral filtering, is designed to rapidly generate output video from the captured data at frame rates fast enough for real-time video analysis tasks such as tracking and surveillance. We evaluate the proposed system using both simulations with ground truth data and on real-world scenes. The accuracy of spectral capture is examined through comparisons with ground truth and with a commercial spectrometer. The utility of this high resolution MS video data is demonstrated on the applications of dynamic white balance adjustment, object tracking, and separating the appearance contributions of different illumination sources. The various high resolution MS video datasets that we captured will be made publicly available to facilitate research on dynamic spectral data analysis.

Keywords

Multispectral video capture Hybrid camera system 

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Chenguang Ma
    • 1
  • Xun Cao
    • 2
  • Xin Tong
    • 3
  • Qionghai Dai
    • 1
  • Stephen Lin
    • 3
  1. 1.Department of AutomationTsinghua UniversityBeijingChina
  2. 2.School of Electronic Science and EngineeringNanjing UniversityNanjingChina
  3. 3.Microsoft Research AsiaBeijingChina