Table of Contents Author Guidelines Submit a Manuscript
International Journal of Reconfigurable Computing
Volume 2012, Article ID 368351, 16 pages
Research Article

Object Recognition and Pose Estimation on Embedded Hardware: SURF-Based System Designs Accelerated by FPGA Logic

Department of Computer Science, Augsburg University of Applied Sciences, An der Hochschule 1, 86161 Augsburg, Germany

Received 4 May 2012; Revised 17 September 2012; Accepted 17 September 2012

Academic Editor: René Cumplido

Copyright © 2012 Michael Schaeferling et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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 medium-size 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.