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     Structure from motion is a technique that attempts to reconstruct the 3D structure of a scene from a sequence of images taken from a camera moving within the scene.  Structure from motion can be used on an Unmanned Aerial Vehicle or Unmanned Ground Vehicle for obstacle detection as well as for path-planning and navigation. The 3D structure of the scene is estimated using the optical flow values found at a set of feature points on the image. 

    We developed a novel multi-frame structure from motion algorithm in which the camera motion and object structure are calculated from optical flow probability distributions instead of a single optical flow estimate at each feature point.  Optical flow distributions of the selected feature points allow us to quantify the accuracy of the optical flow estimate in any direction.  With this additional knowledge, a more accurate structure from motion algorithm is created which relies more heavily on the more accurate optical flow data.  This novel method is designed to use the optical flow values taken from multiple frames of video or an image sequence.  It is an optimal solution to the structure from motion problem with respect to a chosen norm.  We demonstrated that this new method performs significantly better than similar methods which do not use optical flow distributions or do not use multiple frames.

 Graduate Students:

 Paul Merrell and Zhaoyi Wei

  1. D.J. Lee, P.C. Merrell, Z.Y. Wei, and B.E. Nelson, “Two-Frame Structure from Motion Using Optical Flow Probability Distributions for Unmanned Air Vehicle Obstacle Avoidance,” Machine Vision and Applications Journal, vol. 21/3, p. 229-240, April 2010.

  2. D.J. Lee, P.C. Merrell, B.E. Nelson, and Z.Y. Wei, “Multi-Frame Structure from Motion using Optical Flow Probability Distributions,” Journal of Neurocomputing, vol. 72/4-6, p. 1032-1041, January 2009.

  3. P.C. Merrell and D.J. Lee, ”Structure from Motion Using Optical Flow Probability Distributions”, SPIE International Symposium on Defense and Security, Intelligent Computing: Theory and Applications III, vol. 5803-6, p. 39-48, Orlando, Florida, USA, March 28-April 1, 2005.

  4. P. Merrell, D.J. Lee, and R.W. Beard, “Statistical Analysis of Multiple Optical Flow Values for Estimation of Unmanned Air Vehicles Height Above Ground”, SPIE Optics East, Robotics Technologies and Architectures, Intelligent Robots and Computer Vision XXII, vol. 5608, p. 298-305, Philadelphia, PA, USA, October 25-28, 2004.

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