Title
FPGA implementation of a feature detection and tracking algorithm for real-time applications
Abstract
An efficient algorithm to detect, correlate, and track features in a scene was implemented on an FPGA in order to obtain real-time performance. The algorithm implemented was a Harris Feature Detector combined with a correlator based on a priority queue of feature strengths that considered minimum distances between features. The remaining processing of frame to frame movement is completed in software to determine an affine homography including translation, rotation, and scaling. A RANSAC method is used to remove mismatched features and increase accuracy. This implementation was designed specifically for use as an onboard vision solution in determining movement of small unmanned air vehicles that have size, weight, and power limitations.
Year
DOI
Venue
2007
10.1007/978-3-540-76858-6_66
ISVC (1)
Keywords
Field
DocType
feature detection,real time,priority queue
Affine transformation,Computer science,Real-time computing,Homography,Priority queue,Software,Artificial intelligence,Inertial measurement unit,Scaling,Computer vision,RANSAC,Field-programmable gate array,Algorithm
Conference
Volume
ISSN
ISBN
4841
0302-9743
3-540-76857-2
Citations 
PageRank 
References 
13
1.08
8
Authors
5
Name
Order
Citations
PageRank
Beau J. Tippetts11127.62
Spencer G. Fowers2384.74
Kirt D. Lillywhite3354.75
Dah-Jye Lee442242.05
James K. Archibald5632161.01