Papers
5
Total Citations
922
H-Index
4
About
Mohamed E. Hussein is a computer vision and autonomous systems researcher whose work spans human action recognition, motion analysis, and intelligent vehicle control. He is perhaps best known for his pioneering contributions to skeleton-based action recognition, most notably his 2013 paper introducing a temporal hierarchy of covariance descriptors on 3D joint locations, which has garnered over 530 citations and remains a landmark reference in the field. That same year, he proposed the Histogram of Oriented Displacements (HOD) descriptor for encoding human joint trajectories, accumulating over 180 citations and further cementing his influence in human motion analysis. Hussein's research extends naturally into autonomous vehicle technologies; his 2016 review of pure-pursuit-based path tracking techniques has become a widely referenced resource for autonomous driving researchers, with over 175 citations, demonstrating his ability to bridge theoretical foundations with practical engineering challenges. His earlier work on real-time human detection and tracking under uncontrolled camera motion reflects a sustained interest in robust perception systems for robotics and surveillance applications. Collectively, Hussein's contributions illuminate a career dedicated to enabling machines to understand and interact safely with the human world.
Research Focus
Key Achievements
Top Papers
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- 5Development of Lane keeping Controller Using Image processing2 citations · 2018