High Performance Feature Detection on a Reconfigurable Co-Processor

Jia Ming Mar, Alessandro Bissacco, Stefano Soatto, Soheil Ghiasi

Abstract: In this paper, the authors propose a new design for feature detection used for tracking, which eliminates the need of a central computer to complete computations for the feature selection algorithm. Such a system constrains performance due to the delay in which data is transferred from camera to computer for processing. Our design suggests that feature detection computation can be done on a processor within the camera helping to reduce overall computation time for detection and increase performance for overall tracking system. However, these systems are often constrained by the processing power available to the camera. But with Benedetti and Perona's approach to Tomasi and Kanade's detection algorithm, such a design is possible to implement onto a camera system which would eliminate the delay and also improve performance over a tracking system designed on software