Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

Fast Appearance Based Object Recognition: A Hybrid Approach

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

2 Author(s)

Visual object recognition is a useful skill for robots to possess. However, present approaches to the problem do not scale to large numbers of objects (few manage more than 10) and require too much computation for real-time tasks on a robot. This paper presents a hybrid decision tree/support vector machine approach to recognition which is fast, with recognition times under one second. A new test dataset is also presented, consisting of over 100,000 images of Lego bricks, acquired by repeatedly dropping the bricks. The proposed method achieves 96% accuracy on the set of 89 different types of Lego bricks, demonstrating its applicability for large-scale real-time visual object recognition.

Published in:

Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on

Date of Conference:

18-22 April 2005