Hui-Fen Chiang
Papers
1
Total Citations
15
H-Index
1
About
Hui-Fen Chiang is a researcher specializing in computer vision and intelligent surveillance systems, with a particular focus on abnormal event detection using mobile platforms. Her most-cited work, "Abnormal Scene Change Detection from a Moving Camera Using Bags of Patches and Spider-Web Map" (2014, 15 citations), introduces a novel surveillance framework that enables a robot-mounted camera to detect exceptional scene changes as abnormal events—a significant departure from traditional fixed-camera approaches. This research addresses three critical challenges: scene construction, robot localization, and real-time anomaly identification, offering a robust solution for dynamic environments. Chiang’s contributions advance the field of autonomous monitoring by integrating bag-of-patches representations with spider-web mapping techniques, enhancing the ability to detect subtle, context-dependent anomalies. Her work has implications for robotics, security, and smart city applications, demonstrating how mobile vision systems can overcome the limitations of static surveillance. With a focus on practical, deployable systems, Chiang’s research continues to inspire innovations in adaptive, real-world computer vision.
Research Focus
Key Achievements
Top Papers
- 1