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This paper reviews and compares various techniques for detecting and identifying markers in computer vision, highlighting the robustness of digital code-based methods over correlation and topology-based approaches. It discusses the importance of marker design and the performance metrics used to evaluate detection algorithms, including false positive rates and marker library sizes. The findings suggest that sophisticated digital codes enhance reliability, particularly in scenarios involving occlusion and min

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