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A Third Eye for Performance Evaluation in Stereo Sequence Analysis

  • Sandino Morales
  • Reinhard Klette
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5702)

Abstract

Prediction errors are commonly used when analyzing the performance of a multi-camera stereo system using at least three cameras. This paper discusses this methodology for performance evaluation for the first time on long stereo sequences (in the context of vision-based driver assistance systems). Three cameras are calibrated in an ego-vehicle, and prediction error analysis is performed on recorded stereo sequences. They are evaluated using various common stereo matching algorithms, such as belief propagation, dynamic programming, semi-global matching, or graph cut. Performance is evaluated on both synthetic and real data.

Keywords

Root Mean Square Dynamic Programming Algorithm Virtual Image Virtual View Normalize Cross Correlation 
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-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sandino Morales
    • 1
  • Reinhard Klette
    • 1
  1. 1.The .enpeda.. ProjectThe University of AucklandAucklandNew Zealand

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