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Uncertainty and accuracy of vision-based tracking concerning stereophotogrammetry and noise-floor tests

Ngeljaratan Luna, Moustafa Mohamed A.

Metrology and Measurement Systems

2022

Vol. 29, nr 1

75--92

This work proposes a systematic assessment of stereophotogrammetry and noise-floor tests to characterize and quantify the uncertainty and accuracy of a vision-based tracking system. Two stereophotogrammetry sets with different configurations, i.e., some images are designed and their sensitivity is quantified based on several assessments. The first assessment evaluates the image coordinates, stereo angle and reconstruction errors resulting from the stereophotogrammetry procedure, and the second assessment expresses the uncertainty from the variance and bias errors measured from the noise-floor test. These two assessments quantify the uncertainty, while the accuracy of the vision-based tracking system is assessed from three quasi-static tests on a small-scaled specimen. The difference in each stereophotogrammetry set and configuration, as indicated by the stereophotogrammetry and noise-floor assessment, leads to a significant result hat the first stereophotogrammetry set measures the RMSE of 3.6 mm while the second set identifies only 1.6 mm of RMSE. The results of this work recommend a careful and systematic assessment of stereophotogrammetry and noise-floor test results to quantify the uncertainty before the real test to achieve a high displacement accuracy of the vision-based tracking system.

Design and implementation of visual feedback for an active tracking

Żabiński T., Grygiel T., Kwolek B.

Machine Graphics and Vision

2006

Vol. 15, No. 3/4

681-690

Active visual tracking is used to direct the attention of the camera to an object and maintain it in the camera's field of view. A steered camera is used to decrease relative motion of the target in the image plane. This leads to better performance of the mean-shift based tracking algorithm, which requires the object tracked in the current and the previous frame to overlap. A classical PID controller and a nonlinear fuzzy controller have been tested in steering the camera head.