Evaluation of the SIFT Object Recognition Method in Mobile Robots

13 years 5 months ago

Download www.iiia.csic.es

General object recognition in mobile robots is of primary importance in order to enhance the representation of the environment that robots will use for their reasoning processes. Therefore, we contribute reduce this gap by evaluating the SIFT Object Recognition method in a challenging dataset, focusing on issues relevant to mobile robotics. Resistance of the method to the robotics working conditions was found, but it was limited mainly to well-textured objects. Keywords. Computer Vision, Object Recognition, Mobile Robots

Arnau Ramisa, Shrihari Vasudevan, David Aldavert,

Real-time Traffic

Artificial Intelligence | CCIA 2009 | General Object Recognition | Mobile Robots | Object Recognition |

claim paper

» Monte Carlo Localization Using SIFT Features

» Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot

» Improved SIFTFeatures Matching for Object Recognition

» Learning to Select Object Recognition Methods for Autonomous Mobile Robots

» Mobile Museum Guide Based on Fast SIFT Recognition

» Selection of Object Recognition Methods According to the Task and Object Category

» Selection of SIFT feature points for scene description in robot vision

» Active exploration and keypoint clustering for object recognition

Post Info
More Details (n/a)

Added	08 Nov 2010
Updated	08 Nov 2010
Type	Conference
Year	2009
Where	CCIA
Authors	Arnau Ramisa, Shrihari Vasudevan, David Aldavert, Ricardo Toledo, Ramon López de Mántaras

Comments (0)

Sciweavers

Evaluation of the SIFT Object Recognition Method in Mobile Robots

Artificial Intelligence | CCIA 2009 | General Object Recognition | Mobile Robots | Object Recognition |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers