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�������պ����ѧѧ�� 2011, Vol. 37 Issue (9) :1181-1185    DOI:
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�������պ����ѧ ������ʵ������ϵͳ�����ص�ʵ����, ���� 100191
Panoramas subspace based scale invariant feature tracking method
Fan Zhiqiang*
State Key Laboratory of Virtual Reality Technology and Systems, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

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Abstract�� Aiming to panoramas images, a panoramas subspace based scale invariant feature tracking method was proposed which contains an offline process to build feature correspondence between panoramas and original image sequence and an online process to match features based on keyframe recognization. Firstly making full use of the ability of panoramas to cover approximately entire local nature space, a way was given to extend Kd tree to build feature correspondence between panoramas and original image sequence which can efficiently reduce feature redundancy of panoramas and improve the first matching stage-s time. On the basis of this mapping, a voting method was used to recognize keyframe to finish the second matching stage. Through the two feature matching stages above, the aim was reached that converts the feature matching from multiple images to single image to decrease feature number. Experimental results show that the method can efficiently achieve good balance between matching time and stability.
Keywords�� panoramas   Kd tree   scale invariant feature transform   keyframe   voting     
Received 2010-04-26;
Fund:

����863�ƻ�������Ŀ(2009AA012103)

About author: ��־ǿ(1978-),��,ɽ��������,��ʿ��,fanzq@vrlab.buaa.edu.cn.
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Fan Zhiqiang.Panoramas subspace based scale invariant feature tracking method[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2011,V37(9): 1181-1185
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