Object Recognition and Pose Estimation on Embedded Hardware: SURF-Based System Designs Accelerated by FPGA Logic. (6th December 2012)

• Record Type: Journal Article
• Authors: Schaeferling, Michael; Hornung, Ulrich; Kiefer, Gundolf
• Other Names: Cumplido René Academic Editor.
• Is Part Of: International journal of reconfigurable computing. Volume 2012(2012)
• Publication Date: 2012-12-06
• Subjects: Adaptive computing systems -- Periodicals; Adaptive computing systems; Periodicals; 004
• DOI: 10.1155/2012/368351
• Languages: English
• ISSNs: 1687-7195

Abstract

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 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.