id: 06098396
dt: j
an: 06098396
au: Shao, Ling; Zhen, Xiantong; Liu, Yan; Ji, Ling
ti: Human action representation using pyramid correlogram of oriented gradients
    on motion history images.
so: Int. J. Comput. Math. 88, No. 18, 3882-3895 (2011).
py: 2011
pu: Taylor \& Francis, Abingdon
la: EN
cc: 
ut: human action recognition; feature descriptor; pyramid correlogram of
    oriented gradients; motion history image
ci: 
li: doi:10.1080/00207160.2011.582102
ab: Summary: The representation of human actions in video sequences is one of
    the key steps in action classification and recognition, performances of
    which are greatly dependent on the distinctiveness and robustness of
    the descriptors used for representation. In this paper, a novel
    descriptor, named pyramid correlogram of oriented gradients (PCOG), is
    presented for feature representation. PCOG, combined with the motion
    history images, captures both shape and spatial layout of the motion
    and therefore gives more effective and powerful representation for
    human actions and can be used for the detection and recognition of a
    variety of actions. Experiments on challenging action data sets show
    that PCOG performs significantly better than the histogram of oriented
    gradients both as a global descriptor and as a local descriptor.
rv: