By Topic

SIFT-ing through features with ViPR

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)

Recent advances in computer vision have given rise to a robust and invariant visual pattern recognition technology that is based on extracting a set of characteristic features from an image. Such features are obtained with the scale invariant feature transform (SIFT) which represents the variations in brightness of the image around the point of interest. Recognition performed with these features has been shown to be quite robust in realistic settings. This paper describes the application of this particular visual pattern recognition (ViPR) technology to a variety of robotics applications: object recognition, navigation, manipulation, and human-machine interaction. The paper also describes the technology in more detail and presents a business case for visual pattern recognition in the field of robotics and automation

Published in:

Robotics & Automation Magazine, IEEE  (Volume:13 ,  Issue: 3 )