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.
Abstract: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.
Abstract:The problem of finding an appropriate path for a mechanical arm that tries to reach a target among obstacles is one of the most important in fields of automation and robotics. It is both a classic inverse kinematics and collision detection problem. This project aimed to construct a tool to plan a path for an articulated arm through a two-dimensional environment with obstacles. The inverse kinematics problem is addressed by heuristics Bayesian particles filter, and the collision detection problem is solved using computational geometry methods for calculating the free configurations space. The proposed tool has a graphical interface with which you can get information from the designed experiments. The feasibility of this approach and its advantages in complex two-dimensional environments is shown. We proved that good results can be obtained with an appropriate selection of the parameters.
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