TY - GEN
T1 - Robust Stereo Matching Algorithm Based on Spatial Constraints under Rectification
AU - Li, Ziheng
AU - Zheng, Zhao
AU - Liu, Shaojie
AU - Fan, Jingfan
AU - Yang, Jian
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/5/19
Y1 - 2023/5/19
N2 - Medical intelligent navigation systems have attracted increasing attention, and binocular optical tracking systems being an important component to ensure accurate tracking navigation. However, ghost markers may appear when there are multiple markers on the same plane, which can result in tracking errors and significantly impact the surgical process. In this paper, we propose a robust stereo matching algorithm based on spatial constraints under rectification. The algorithm is verified using a binocular vision system based on Xilinx Zynq-7020 platform of field-programmable gate array (FPGA), which meets the requirement of fast, real-time tracking of multiple instruments. The used matching algorithm has a tracking processing time of only 107 under four surgical instruments, which is 82.46% higher than the epipolar geometry method. Furthermore, compared with the traditional sequential matching method, this method improves the tracking failure rate by 6.46% for tracking four instruments, effectively avoiding false matching caused by the appearance of ghost markers.
AB - Medical intelligent navigation systems have attracted increasing attention, and binocular optical tracking systems being an important component to ensure accurate tracking navigation. However, ghost markers may appear when there are multiple markers on the same plane, which can result in tracking errors and significantly impact the surgical process. In this paper, we propose a robust stereo matching algorithm based on spatial constraints under rectification. The algorithm is verified using a binocular vision system based on Xilinx Zynq-7020 platform of field-programmable gate array (FPGA), which meets the requirement of fast, real-time tracking of multiple instruments. The used matching algorithm has a tracking processing time of only 107 under four surgical instruments, which is 82.46% higher than the epipolar geometry method. Furthermore, compared with the traditional sequential matching method, this method improves the tracking failure rate by 6.46% for tracking four instruments, effectively avoiding false matching caused by the appearance of ghost markers.
KW - Ghost markers
KW - mismatch
KW - multi-instrument
KW - rectification
KW - stereo matching
UR - http://www.scopus.com/inward/record.url?scp=85179889595&partnerID=8YFLogxK
U2 - 10.1145/3604078.3604156
DO - 10.1145/3604078.3604156
M3 - Conference contribution
AN - SCOPUS:85179889595
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 15th International Conference on Digital Image Processing, ICDIP 2023
PB - Association for Computing Machinery
T2 - 15th International Conference on Digital Image Processing, ICDIP 2023
Y2 - 19 May 2023 through 22 May 2023
ER -