id: 06107653
dt: j
an: 06107653
au: Sheng, Hao; Li, Chao; Ouyang, Yuanxin; Xiong, Zhang
ti: A precise approach to tracking dim-small targets using spectral fingerprint
    features.
so: Front. Comput. Sci. 6, No. 5, 527-536 (2012).
py: 2012
pu: Higher Education Press, Beijing; Springer, Berlin
la: EN
cc: 
ut: dim-small target; precise tracking; spectral fingerprint features; LPF
    algorithm for spectral tracking
ci: 
li: doi:10.1007/s11704-012-1106-2
ab: Summary: A precise method for accurately tracking dim-small targets, based
    on spectral fingerprint is proposed where traditional full color
    tracking seems impossible. A fingerprint model is presented to
    adequately extract spectral features. By creating a multidimensional
    feature space and extending the limited RGB information to the
    hyperspectral information, the improved precise tracking model based on
    a nonparametric kernel density estimator is built using the probability
    histogram of spectral features. A layered particle filter algorithm for
    spectral tracking is presented to avoid the object jumping abruptly.
    Finally, experiments are conducted that show that the tracking
    algorithm with spectral fingerprint features is accurate, fast, and
    robust. It meets the needs of dim-small target tracking adequately. Hao
    Sheng Received his BS and PhD degrees from the School of Computer
    Science and Engineering of Beihang University in 2003 and 2009,
    respectively. Now he is an assistant professor at Beihang University.
    He is working on computer vision, intelligent transportation systems,
    and hyperspectral remote sensing.
rv: