Research

In this study, real-time feature point tracking at 1000 fps was performed by implementing a feature point tracking algorithm on a high-speed vision platform, which is improved for hardware integration and high-speed processing at real time. To solve the problems of high-speed hardware processing with less memory consumption and low computational load, we improved the feature point tracking algorithm by considering (1) maximum value search in divided block regions, and (2) correspondence in limited block regions by assuming high frame rates. The processing flow of the improved algorithm in the below figure.


The high-speed vision platform on which the improved algorithm is hardware-implemented can be used to track feature points of 1024x1024 pixel images at 1000 fps. By considering fast-moving objects in the real world, we verified the performance of our developed real-time feature point tracking system.