ORB feature extraction and matching in hardware

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The ORB (Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features)) feature extractor is the state of the art in wide baseline matching with sparse image features for robotic vision. All previous implementations have employed general-purpose computing hardware, such as CPUs and GPUs. This work seeks to investigate the applicability of special-purpose computing hardware, in the form of Field-Programmable Gate Arrays (FPGAs), to the acceleration of this problem. FPGAs offer lower power consumption and higher frame rates than general hardware. A working implementation on an Altera Cyclone II (a low-cost FPGA suitable for development work, and available with a camera and screen interface) is described.
Original languageEnglish
Title of host publicationAustralasian Conference on Robotics and Automation, ACRA 2015
Subtitle of host publication2-4 December 2015; Canberra, Australia
EditorsRobert Mahony, Jonghyuk Kim, Hongdong Li
Place of PublicationCanberra ACT Australia
PublisherAustralian Robotics and Automation Association (ARAA)
Number of pages10
ISBN (Electronic)9780980740462
ISBN (Print)9781510819269
Publication statusPublished - 2015
EventAustralasian Conference on Robotics and Automation 2015 - Australian National University (ANU), Canberra, Australia
Duration: 2 Dec 20154 Dec 2015


ConferenceAustralasian Conference on Robotics and Automation 2015
Abbreviated titleACRA 2015
Internet address

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