M. Hasanuzzaman
Papers
11
Total Citations
133
H-Index
6
About
M. Hasanuzzaman is a pioneering researcher in the field of human-robot interaction (HRI), with a career spanning over two decades dedicated to developing intelligent, vision-based systems that enable seamless communication between humans and robots. His foundational work, beginning in the mid-2000s, established robust frameworks for gesture and facial recognition using techniques such as skin color segmentation, Principal Component Analysis, and subspace methods — forming the backbone of intuitive robot control systems. His most cited work, "Adaptive Visual Gesture Recognition for Human-Robot Interaction Using a Knowledge-Based Software Platform" (2007, 60 citations), exemplifies his innovative integration of machine learning with knowledge-based architectures to achieve adaptive, real-time gesture recognition. Hasanuzzaman further advanced the field through the development of the Software Platform for Agents and Knowledge Management (SPAK), enabling sophisticated multi-robot coordination and person-centric interaction. His later contributions, including a Kinect-based 3D gesture recognition system (2018), demonstrate his continued evolution with emerging sensor technologies. With a cumulative citation count exceeding 130, his body of work has meaningfully shaped the trajectory of HRI research, making him a noteworthy figure for students and practitioners exploring robotics, computer vision, and intelligent systems.
Research Focus
Key Achievements
Top Papers
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- 2Gesture based human-robot interaction using a frame based software platform25 citations · 2005
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- 9Vision based gesture recognition for human-robot symbiosis3 citations · 2007
- 10User, Gesture and Robot Behaviour Adaptation for Human-Robot Interaction2 citations · 2012