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Adaptive object tracking algorithm based on eigenbasis space and compressive sampling
J. Li
*
,
J. Wang
*
Corresponding author for this work
School of Automation
Research output
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Contribution to journal
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Article
›
peer-review
5
Citations (Scopus)
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Computer Science
Tracking Algorithm
100%
Tracking Method
100%
Tracking Object
100%
Dimensional Subspace
100%
Compressive Sampling
100%
Experimental Result
50%
Compressive Sensing
50%
Image Processing
50%
Image Transmission
50%
Appearance Variation
50%
Image Storage
50%
Pose Variation
50%
Engineering
Compressive Sampling
100%
Dimensional Subspace
100%
Object Tracking Algorithm
100%
Experimental Result
50%
Obtains
50%
Target Tracking
50%
Image Processing
50%
Compressive Sensing
50%
Image Transmission
50%
Tracking Algorithm
50%
Pose Variation
50%
Image Storage
50%