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High-performance tracking system

  • Jiantao Huang
  • Jian-zhao Wang
Session IA1a — Robot Navigation & Tracking
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)

Abstract

In this paper, we describe how reliable SSD feature selection, feature tracking and feature monitoring can be realized and interleaved into a high-performance system with no special-purpose hardware. We consider image brightness and contrast changes in the tracking system which haven't been treated before. We find the decoupled system outperforms the usual coupled system. We perform this calculation at multiple levels of resolution, leading to an adaptive algorithm for tracking both slow and fast motions. A new interpretation of feature selection is based on the trade off between noise resistance and linearization error. The overcorrectness problem in feature monitoring is addressed.

Keywords

Feature Selection Image Noise Image Region Visual Tracking Minimum Eigenvalue 
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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Jiantao Huang
    • 1
  • Jian-zhao Wang
    • 2
  1. 1.Yale UniversityNew HavenUSA
  2. 2.Polytechnic UniversityBrooklynUSA

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