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3D convolutional networks is a good means to perform tasks such as videosegmentation into coherent spatio-temporal chunks and classification of themwith regard to a target taxonomy. In the chapter we are interested in theclassification of continuous video takes with repeatable actions, such asstrokes of table tennis. Filmed in a free marker less ecological environment,these videos represent a challenge from both segmentation and classificationpoint of view. The 3D convnets are an efficient tool for solving these problemswith window-based approaches.

3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition