Multiple 3D object position estimation and tracking using double filtering on multi-core processor

We present a new algorithm to tracking multiple 3D objects that has robustness, real-time processing ability and fast object registration. Usually, many augmented reality applications want to track 3D object using natural features in real-time, more accuracy and want to register target object immedi...

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Bibliographic Details
Published in:Multimedia tools and applications 2013-03, Vol.63 (1), p.161-180
Main Authors: Park, Jin-hyung, Rho, Seungmin, Jeong, Chang-sung, Kim, Jongik
Format: Article
Language:English
Subjects:
3-D graphics
Accuracy
Algorithms
Analysis
Augmented reality
Computer Communication Networks
Computer engineering
Computer Science
Data Structures and Information Theory
Filtering
Filtration
Kalman filters
Localization
Methods
Multimedia computer applications
Multimedia Information Systems
Parks & recreation areas
Real time
Registers
Registration
Robustness
Special Purpose and Application-Based Systems
Studies
Three dimensional
Tracking
Tracking control systems
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Description
Summary:We present a new algorithm to tracking multiple 3D objects that has robustness, real-time processing ability and fast object registration. Usually, many augmented reality applications want to track 3D object using natural features in real-time, more accuracy and want to register target object immediately in few seconds. Prevalent object tracking algorithm uses FERN for feature extraction that takes long time to register and learning target object for high quality performance. Our method provides not only high accuracy but also fast target object registering time about 0.3 ms in same environment and real-time processing. These features are presented by using SURF, ROI, double robust filtering and optimized multi-core parallelization. Using our methods, tracking multiple 3D objects with fast and high accuracy is available.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-012-1029-9