Paper
8 July 2022 An object tracking algorithm with adaptive template updating for visual tracking measurement system
Xiaoyun Chen, Jiarui Lin, Yanbiao Sun, Ze Yang, Jigui Zhu
Author Affiliations +
Abstract
This paper proposes a novel adaptive template updating method with continuous variational spatial-temporal characteristics, which is utilized as a part of visual object tracking in the measurement process of the vision measurement system. The measurement system is set up by cameras and turntables to catch the profile of a moving object in largescale space. Among all steps, the proposed method is applied to positioning the object. In order to enhance the spatial constraints of the tracking algorithm to make the measurement results more reliable, the Average Peak-to-Correlation Energy (APCE) whose property includes spatial information is used as a part of the learning rate in the template updating step. Experiments show that the results calculated by the proposed method have a smoother profile. With the comparison of the fixed distances measured by Leica T-Mac, the proposed method applied in the system performed higher accuracy.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoyun Chen, Jiarui Lin, Yanbiao Sun, Ze Yang, and Jigui Zhu "An object tracking algorithm with adaptive template updating for visual tracking measurement system", Proc. SPIE 12282, 2021 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 122820A (8 July 2022); https://doi.org/10.1117/12.2613680
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KEYWORDS
Optical tracking

Detection and tracking algorithms

Distance measurement

Motion measurement

Cameras

Image processing

Image filtering

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