Paper Info
Title
Sift Features For Object Recognition And Tracking Within The Ivsee System
Abstract
In this paper, we study the feasibility of SIFT features for the tasks of object recognition and tracking within the framework of the IVSEE system design. The IVSEE system is intended to imitate the early functionalities of the human visual system in enclosed environments. The goal of this system is to be able to; perform basic object recognition, determine object states and spatial interrelations, and all of this engaged with a purposive system behavior (e.g. object tracking). To implement this system, we turn to well-known and state-of-the-art techniques from the literature, and choose SIFT features for the stages of object extraction and recognition. We have performed (and present here) experimental work carried out to determine the adequacy of these features for the system goals. Results confirm SIFT features as a good implementation choice.
Year
DOI
Venue
2008
10.1109/ICPR.2008.4761150
19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6
Keywords
Field
DocType
system design,human visual system,databases,object recognition,computer vision,object tracking,lighting,tracking,machine vision,feature extraction
Scale-invariant feature transform,Computer vision,3D single-object recognition,Machine vision,Pattern recognition,Human visual system model,Computer science,Feature extraction,Haar-like features,Video tracking,Artificial intelligence,Cognitive neuroscience of visual object recognition
Conference
ISSN
Citations 
PageRank 
1051-4651
4
0.41
References 
Authors
3
1
Name
Order
Citations
PageRank
Fernando López-García151.78