Render: Predicting Scenes

  • Mark R. Stevens
  • J. Ross Beveridge
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 589)


The main goal of scene prediction is to generate an image of a virtual world which can be directly compared to an image from a real sensor. How accurate the prediction must be in order for the two images to be comparable depends upon the specific application domain and the comparison metric used. Intuitively, the closer the prediction mirrors reality, the higher the chance the RMR (Render-Match-Refine) algorithm will be successful. Unfortunately, generating a perfect prediction is an impossible task. Information such as the background scene context, lighting, and complex camera distortions are difficult to model and often cannot be inferred from a static sensor image. Therefore, the role of prediction is to produce an image, at the resolution of the real sensor, that provides information exploitable by the subsequent stages of the RMR method (matching and refinement).


Object Recognition Training Image Label Image Scene Point Integrate Graphic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Mark R. Stevens
    • 1
  • J. Ross Beveridge
    • 2
  1. 1.Worcester Polytechnic InstituteUSA
  2. 2.Colorado State UniversityUSA

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