Human action search based on dynamic shape volumes

Abstract

In this paper, an interactive system for human action video search is developed based on the dynamic shape volumes. The user is allowed to create a search query by freely and continuously posing any number of actions in front of the Kinect sensor. For the captured query video sequence and each data stream of the human action video database, we extracted useful shape properties on the basis of space-time volumes by exploiting the solution to the Poisson equation. Different from conventional learning-based human action recognition techniques, we apply approximate string matching (ASM) to achieve local alignment for the matching of two video sequences. The experiments demonstrate the effectiveness of our system in support of the user's search task. © Springer-Verlag 2013.