Task and Context aware Performance Evaluation of Computer Vision Algorithms

Authors

  • Wolfgang Ponweiser
  • Markus Vincze

DOI:

https://doi.org/10.2390/biecoll-icvs2007-123

Keywords:

automatic system generation, performance evaluation, task and context dependency, multi objective optimization, DDC: 004 (Data processing, computer science, computer systems)

Abstract

Developing a robust computer vision algorithm is very difficult because of the enormous variation of visual conditions. A systems technology solution to this challenge is an automatic selection and configuration of different existing algorithms according to the task and context of arbitrary applications. This paper presents a first attempt to generate the required mapping between the task/context to the optimal algorithm and algorithm configuration. This mapping is based on an extensive performance evaluation. To practically handle the exhaustive search for optimal solutions a new optimization challenge the Multiple-Multi Objective Optimization (M-MOP) and an according solution based on genetic algorithms is developed and evaluated. The results show the robustness of the approach and guide further development towards an automatic vision system generation.

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Published

2007-12-31

Issue

Section

The 5th International Conference on Computer Vision Systems