Christos Ttofis
Papers
3
Total Citations
32
H-Index
3
About
Christos Ttofis is a researcher specializing in embedded computer vision, reconfigurable hardware, and real-time 3D perception for robotics and security systems. His work focuses on designing hardware-efficient architectures that enable high-performance, low-power object detection and depth estimation using stereoscopic vision. His most-cited paper (2013, 17 citations) introduces a hardware architecture for real-time object detection that fuses depth and edge information, addressing the critical need for accurate video analysis in embedded systems. A second influential work (2015, 12 citations) presents a hardware-efficient design for accurate real-time disparity map estimation, which is essential for depth perception in autonomous platforms. Ttofis also contributed to real-time obstacle avoidance for mobile robots (2015, 3 citations), demonstrating a complete prototyping platform for evaluating stereoscopic vision on reconfigurable hardware. His contributions are particularly notable for bridging the gap between algorithmic accuracy and hardware constraints, enabling practical deployment in applications such as autonomous navigation, space exploration, and transportation. Ttofis’s research continues to impact the development of intelligent, energy-efficient vision systems for next-generation robotics and security technologies.
Research Focus
Key Achievements
Top Papers
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