Ontology type: schema:Chapter
2016
AUTHORSHai-Hong Phan , Ngoc-Son Vu , Vu-Lam Nguyen , Mathias Quoy
ABSTRACTIn this paper, we present a novel descriptor for human action recognition, called Motion of Oriented Magnitudes Patterns (MOMP), which considers the relationships between the local gradient distributions of neighboring patches coming from successive frames in video. The proposed descriptor also characterizes the information changing across different orientations, is therefore very discriminative and robust. The major advantages of MOMP are its very fast computation time and simple implementation. Subsequently, our features are combined with an effective coding scheme VLAD (Vector of locally aggregated descriptors) in the feature representation step, and a SVM (Support Vector Machine) classifier in order to better represent and classify the actions. By experimenting on several common benchmarks, we obtain the state-of-the-art results on the KTH dataset as well as the performance comparable to the literature on the UCF Sport dataset. More... »
PAGES168-177
Advances in Visual Computing
ISBN
978-3-319-50831-3
978-3-319-50832-0
http://scigraph.springernature.com/pub.10.1007/978-3-319-50832-0_17
DOIhttp://dx.doi.org/10.1007/978-3-319-50832-0_17
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