The choice of the parameters has strong influence on the quality of the results obtained by the application of algorithms. Most researchers tend to select the values of their parameters in long and tedious trial and error approaches. Although, some methods have been developed for automatic parameter selection, they have not been widely used in the computer vision area. This paper presents the design of a general purpose framework for automatic parameter selection through a case study: a human limb tracking algorithm developed for applications that will be used in rehabilitation scenarios with low cost equipment. The tracking algorithm first detects the limb by using a skin segmentation approach, then the position of an idealized limb model is updated using Simulated Annealing. The framework for automatic parameter selection treats each parameter from the tracking algorithm according to its domain and uses a modified version of Harmony Search Optimization algorithm that includes a dominance criterion. The obtained results are presented as well and show that selected parameters behave well for the case of study.
Automatic parameter selection; Harmony Search Optimization; Simulated Annealing; Human limb tracking.
Oscar L. VERA-PÉREZ, Alejandro MESEJO-CHIONG, Antoni JAUME-I-CAPÓ, Manuel GONZÁLEZ-HIDALGO, "Automatic Parameter Configuration: A Case Study on a Rehabilitation Oriented Human Limb Tracking Algorithm", Studies in Informatics and Control, ISSN 1220-1766, vol. 23(1), pp. 87-96, 2014. https://doi.org/10.24846/v23i1y201409
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