Smart Vision & Robotic Sensing

Professor, Robotics Laboratory
Smart Innovation Program, Graduate School of Advanced Science and Engineering
Hiroshima University
>> Research Contents
In order to establish high-speed robot senses that are much faster than human senses, we are conducting research and development of information systems and devices that can achieve real-time image processing at 1000 frames/s or greater. As well as integrated algorithms to accelerate sensor information processing, we are also studying new sensing methodologies based on vibration and flow dynamics; they are too fast for humans to sense.

High-frame-rate Target Tracking with CNN-based Object Recognition

We propose an intelligent and fast tracking method for robust trackability against appearance changes. The method hybridizes a correlation-based tracking algorithm operating at hundreds of frames per second (fps) with a deep learning-based recognition algorithm operating at dozens of fps. A prototype intelligent mechanical tracking system was developed by implementing our hybridized tracking algorithm on a 500-fps vision platform. A complex-shaped target can be robustly tracked at the center of the camera view in real time by controlling a pan-tilt active vision system with 500 Hz visual feedback. The tracking performance of our proposed algorithm was verified by showing several experimental results for pre-learned objects, which were quickly manipulated against complex backgrounds.





AVI movie(23.3 MB)
demo video


  • Mingjun Jiang, Yihao Gu, Takeshi Takaki, and Idaku Ishii, High-frame-rate Target Tracking with CNN-based Object Recognition, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 599-606, 2018.