Yongdian Sun

Papers

Total Citations

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About

Yongdian Sun is a researcher focused on advancing human-machine interaction through computer vision, with a particular emphasis on hand tracking and gesture recognition. Their most cited work, "Visual Hand Tracking on Depth Image using 2-D Matched Filter" (2019), addresses a critical challenge in the field: achieving accurate hand detection without the heavy computational demands of traditional machine learning approaches. By proposing a 2-D matched filter method applied directly to depth images, Sun's work offers a more efficient alternative that reduces the need for extensive data collection and processing resources. This contribution is especially valuable for real-time applications where computational efficiency is paramount. With 6 citations, this paper has provided a foundation for researchers seeking lightweight, practical solutions in visual tracking. Sun's research sits at the intersection of signal processing and interactive systems, aiming to make human-machine interfaces more responsive and accessible. Their work continues to inspire developments in low-resource hand tracking, demonstrating that effective interaction can be achieved without sacrificing speed or accuracy.