Description: A subspace t racking method is proposed to t rack target s under complex environment s. First ,
target is represented by subspace histogram of oriented gradient descriptor , which is comp uted by
projecting histograms of oriented gradient descriptor to a subspace , t hat is built f rom a large set of
t raining samples before t racking. Then an integral histogram met hod is incorporated to reduce the
comp utational complexity. By t hese , t he t racking problem is formulated as a state inference problem
under t he particle filter f ramework of target motion parameter estimation.
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