Object recognition and pose estimation on embedded hardware: SURF-based system designs accelerated by FPGA logic

Authors:
Michael Schaeferling;Ulrich Hornung;Gundolf Kiefer
Affiliations:
Department of Computer Science, Augsburg University of Applied Sciences, Augsburg, Germany;Department of Computer Science, Augsburg University of Applied Sciences, Augsburg, Germany;Department of Computer Science, Augsburg University of Applied Sciences, Augsburg, Germany
Venue:
International Journal of Reconfigurable Computing - Special issue on Selected Papers from the 2011 International Conference on Reconfigurable Computing and FPGAs (ReConFig 2011)
Year:
2012

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Abstract

State-of-the-art object recognition and pose estimation systems often utilize point feature algorithms, which in turn usually require the computing power of conventional PC hardware. In this paper, we describe two embedded systems for object detection and pose estimation using sophisticated point features. The feature detection step of the "Speeded-up Robust Features (SURF)" algorithm is accelerated by a special IP core. The first system performs object detection and is completely implemented in a single mediumsize Virtex-5 FPGA. The second system is an augmented reality platform, which consists of an ARM-based microcontroller and intelligent FPGA-based cameras which support the main system.