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Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram
[chapter]
2013
Lecture Notes in Computer Science
Classifying realistic human actions in video remains challenging for existing intro-variability and inter-ambiguity in action classes. Recently, Spatial-Temporal Interest Point (STIP) based local features have shown great promise in complex action analysis. However, these methods have the limitation that they typically focus on Bag-of-Words (BoW) algorithm, which can hardly discriminate actions' ambiguity due to ignoring of spatial-temporal occurrence relations of visual words. In this paper,
doi:10.1007/978-3-642-37431-9_33
fatcat:ysbswllgcff4pkxapkwlj4wv7a