In this work we start investigating the use of appropriately learnt space-time primitives for modeling upper body human actions. As a study case we consider cooking activities which may undergo large intra class variations and are characterized by subtle details, observed by different view points. With a BoK procedure we quantize each video frame with respect to a dictionary of meaningful space-time primitives, then we derive time series that measure how the presence of different primitives evolves over time. The preliminary experiments we report are very encouraging on the discriminative power of the representation, also speaking in favor of the tolerance to view point changes.
CITATION STYLE
Malafronte, D., Goyal, G., Vignolo, A., Odone, F., & Noceti, N. (2017). Investigating the use of space-time primitives to understand human movements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10484 LNCS, pp. 40–50). Springer Verlag. https://doi.org/10.1007/978-3-319-68560-1_4
Mendeley helps you to discover research relevant for your work.