Multimedia Tools and Applications

, Volume 63, Issue 1, pp 161–180 | Cite as

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

Article

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.

Keywords

Augment reality Kalman filter Object tracking Parallel processing Robust filtering 3D estimation 

Notes

Acknowledgement

This research was supported by Samsung Electronics, MKE(Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2010-C1090-1001-0008) and Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0020522).

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.School of Electric Electrical EngineeringKorea UniversitySeoulSouth Korea
  2. 2.Division of Information and CommunicationBaekseok UniversityCheonanSouth Korea
  3. 3.Division of Computer Science & EngineeringChonbuk National UniversityChonbukSouth Korea

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