Model-based Test-Case Generation for Testing Robustness of Vision Components of Robotic Systems
Résumé
This extended abstract outlines a model-based approach for generating test data to assess the robustness of computer vision (CV) solutions with respect to a given task or application. The outlined approach enables the automatic generation of test data with a measurable coverage of optical situations both typical as well as critical for a given application. In addition, expected results are generated, all with almost no manual effort.
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