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Large head movement tracking using sift-based registration

Published: 29 September 2007 Publication History

Abstract

Although there exists dozens of vision based 3D head tracking methods, none of them considers the problem of large motion, especially the movement along the Z axis. In this paper we propose a novel tracking method to handle this problem by using Scale Invariant Feature Transform (SIFT) based registration algorithm. Salient SIFT features are first detected and tracked between two images, and then the 3D points corresponding to these features are obtained from a stereo camera. With these 3D points, a registration algorithm in a RANSAC framework is employed to detect the outliers and estimate the head pose. Performance evaluation shows an accurate pose recovery (3° RMS) when the head has large motion, even with movement along the Z axis was about 150 cm.

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Cited By

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  • (2023)Self-Attention Mechanism-Based Head Pose Estimation Network with Fusion of Point Cloud and Image FeaturesSensors10.3390/s2324989423:24(9894)Online publication date: 18-Dec-2023
  • (2018)Multi-layer CNN Features Aggregation for Real-time Visual Tracking2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8546079(2404-2409)Online publication date: Aug-2018
  • (2018)Evolving Head Tracking Routines With Brain ProgrammingIEEE Access10.1109/ACCESS.2018.28316336(26254-26270)Online publication date: 2018
  • Show More Cited By

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cover image ACM Conferences
MM '07: Proceedings of the 15th ACM international conference on Multimedia
September 2007
1115 pages
ISBN:9781595937025
DOI:10.1145/1291233
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 September 2007

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Author Tags

  1. SIFT
  2. head track
  3. large motion
  4. registration

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all
  • (2023)Self-Attention Mechanism-Based Head Pose Estimation Network with Fusion of Point Cloud and Image FeaturesSensors10.3390/s2324989423:24(9894)Online publication date: 18-Dec-2023
  • (2018)Multi-layer CNN Features Aggregation for Real-time Visual Tracking2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8546079(2404-2409)Online publication date: Aug-2018
  • (2018)Evolving Head Tracking Routines With Brain ProgrammingIEEE Access10.1109/ACCESS.2018.28316336(26254-26270)Online publication date: 2018
  • (2018)Multiple-Gaze Geometry: Inferring Novel 3D Locations from Gazes Observed in Monocular VideoComputer Vision – ECCV 201810.1007/978-3-030-01225-0_38(641-659)Online publication date: 6-Oct-2018
  • (2017)Real-Time Head Pose Estimation Framework for Mobile DevicesMobile Networks and Applications10.1007/s11036-016-0801-x22:4(634-641)Online publication date: 1-Aug-2017
  • (2016)A novel 2D/3D database with automatic face annotation for head tracking and pose estimationComputer Vision and Image Understanding10.5555/2951132.2951428148:C(201-210)Online publication date: 1-Jul-2016
  • (2016)Evaluation of head pose estimation methods for a non-cooperative biometric system2016 MIXDES - 23rd International Conference Mixed Design of Integrated Circuits and Systems10.1109/MIXDES.2016.7529773(394-398)Online publication date: Jun-2016
  • (2016)In-plane face orientation estimation in still imagesMultimedia Tools and Applications10.1007/s11042-015-2699-x75:13(7799-7829)Online publication date: 1-Jul-2016
  • (2015)Head Motion Modeling for Human Behavior Analysis in Dyadic InteractionIEEE Transactions on Multimedia10.1109/TMM.2015.243267117:7(1107-1119)Online publication date: Jul-2015
  • (2015)Usability of Pilot's Gaze in Aeronautic Cockpit for Safer AircraftProceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems10.1109/ITSC.2015.252(1545-1550)Online publication date: 15-Sep-2015
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