Weihua Yin

Papers

Total Citations

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About

Weihua Yin is a researcher whose work lies at the intersection of computer vision, robotics, and artificial intelligence, with a particular focus on enabling machines to perceive and anticipate human motion. His most-cited paper, "Human Motion Prediction Based on Visual Tracking" (2019), addresses a critical challenge in human-robot interaction: how autonomous systems can forecast human movements from visual data to navigate safely and collaborate effectively. This work, which has garnered 2 citations, integrates techniques from visual tracking, feature extraction, and neural networks to improve motion prediction in dynamic environments. While his citation count is modest, Yin’s research contributes to foundational problems in mobile robotics, including path planning, motion control, and SLAM, where understanding human intent is essential. His broader interests span autonomous aerial vehicles and robot vision, reflecting a commitment to building intelligent systems that operate seamlessly alongside people. For students and researchers exploring the convergence of AI and robotics, Yin’s work offers a practical lens on how visual tracking can enhance predictive capabilities, laying groundwork for safer, more responsive autonomous agents in real-world settings.