High-Speed videography using a dense camera array

  • Authors:

  • Bennett Wilburn;Neel Joshi;Vaibhav Vaish;Marc Levoy;Mark Horowitz

  • Affiliations:

  • Department of Electrical Engineering, Stanford University, Stanford, CA;Department of Computer Science, Stanford University, Stanford, CA;Department of Computer Science, Stanford University, Stanford, CA;Department of Computer Science, Stanford University, Stanford, CA;Department of Electrical Engineering, Stanford University, Stanford, CA

  • Venue:
  • CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
  • Year:
  • 2004

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Abstract

We demonstrate a system for capturing multithousand frame-per-second (fps) video using a dense array of cheap 30fps CMOS image sensors. A benefit of using a camera array to capture high-speed video is that we can scale to higher speeds by simply adding more cameras. Even at extremely high frame rates, our array architecture supports continuous streaming to disk from all of the cameras. This allows us to record unpredictable events, in which nothing occurs before the event of interest that could be used to trigger the beginning of recording. Synthesizing one high-speed video sequence using images from an array of cameras requires methods to calibrate and correct those cameras' varying radiometric and geometric properties. We assume that our scene is either relatively planar or is very far away from the camera and that the images can therefore be aligned using projective transforms. We analyze the errors from this assumption and present methods to make them less visually objectionable. We also present a new method to automatically color match our sensors. Finally, we demonstrate how to compensate for spatial and temporal distortions caused by the electronic rolling shutter, a common feature of low-end CMOS sensors.