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In collaborative robotics, human tracking problems are considered as one of the major problems. In some of our recent works, we demonstrated the ways to address this problem by the use of CFAsT-Match algorithm in our real-world shoe detection problem. This paper focuses on a study of performance of CFAsT-Match algorithm with respect to the change of parameters values used in CFAsT-Match. Instead of using a particular scaling factor for dimensions of affine transformations, we set four different parameters taking different values, and tried to find how sensitive are those parameters for CFAsT-Match algorithm, while dealing with our challenging and characteristically diverse datasets. Study of performance of the algorithm for different values of parameters and for different characteristics of images shows the varying sensitivity of those parameters under different challenging scenarios.

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Parameter Sensitivity Analysis for Branch-And-Bound Algorithm-Based CFAsT-Match Approach for Shoe Detection in Collaborative Robotics

  • 会议论文

  • 发表日期：

    2025年

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  • Sayantan Chakraborty,
  • Pritam Paral,
  • Amitava Chatterjee

摘要

In collaborative robotics, human tracking problems are considered as one of the major problems. In some of our recent works, we demonstrated the ways to address this problem by the use of CFAsT-Match algorithm in our real-world shoe detection problem. This paper focuses on a study of performance of CFAsT-Match algorithm with respect to the change of parameters values used in CFAsT-Match. Instead of using a particular scaling factor for dimensions of affine transformations, we set four different parameters taking different values, and tried to find how sensitive are those parameters for CFAsT-Match algorithm, while dealing with our challenging and characteristically diverse datasets. Study of performance of the algorithm for different values of parameters and for different characteristics of images shows the varying sensitivity of those parameters under different challenging scenarios.