This paper describes the complex object distance measuring algorithm for the stereoscopic real-time onboard vision system. This complex algorithm includes two correlation-based algorithms with the different performance complexity and accuracy. The most accurate basic algorithm is a two-dimensional template matching procedure. The other basic algorithm is one-dimensional matching algorithm that used cumulative images as an input. The switching between the algorithms is based on the proposed algorithm performance indicator. This indicator is based on the mean object and background brightness comparison. The experimental research was performed using a set of artificial and natural video sequences. The proposed complex estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.
Valery V. Strotov, Sergey A. Smirnov, Simon E. Korepanov, and Alexey V. Cherpalkin, "Object distance estimation algorithm for real-time FPGA-based stereoscopic vision system," Proc. SPIE 10792, High-Performance Computing in Geoscience and Remote Sensing VIII, 107920A (Presented at SPIE Remote Sensing: September 13, 2018; Published: 9 October 2018); https://doi.org/10.1117/12.2324851.
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