Task and Context aware Performance Evaluation of Computer Vision Algorithms
Schlagworte: automatic system generation, performance evaluation, task and context dependency, multi objective optimization, DDC: 004 (Data processing, computer science, computer systems)
AbstractDeveloping 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.
The 5th International Conference on Computer Vision Systems