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

Authors:
Jin-Hyung Park;Seungmin Rho;Chang-Sung Jeong;Jongik Kim
Affiliations:
School of Electric Electrical Engineering, Korea University, Seoul, South Korea;Division of Information and Communication, Baekseok University, Cheonan, South Korea;School of Electric Electrical Engineering, Korea University, Seoul, South Korea;Division of Computer Science & Engineering, Chonbuk National University, Chonbuk, South Korea
Venue:
Multimedia Tools and Applications
Year:
2013

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Abstract

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.