Jun-Wei Hsieh

Papers

Total Citations

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About

Jun-Wei Hsieh is a leading researcher in computer vision and intelligent surveillance systems, with a focus on mobile robotics and pattern recognition. His work bridges the gap between static and dynamic scene analysis, pioneering methods for abnormal event detection from moving cameras. In his highly cited 2014 paper, Hsieh introduced a novel surveillance framework using "bags of patches" and a "spider-web map" to detect exceptional scene changes from a robot-mounted camera—a significant departure from traditional fixed-camera systems. This work addresses critical challenges in scene construction and robot localization, earning 15 citations for its practical impact on autonomous monitoring. Earlier, Hsieh made notable contributions to automated retail technology with his 2005 study on camera-based bar code recognition using neural networks. This work overcame the distance constraints of conventional laser readers, demonstrating how neural networks could enable flexible, image-based scanning. With a career dedicated to advancing real-world computer vision applications, Hsieh’s research continues to influence the development of smarter, more adaptive surveillance and recognition systems.