A sketch-based approach for detecting common human actions

Abstract

We present a method for detecting common human actions in video, common to athletics and surveillance, using intuitive sketches and motion cues. The framework presented in this paper is an automated end-to-end system which (1) interprets the sketch input, (2) generates a query video based on motion cues, and (3) incorporates a new content- based action descriptor for matching. We apply our method to a publicly- available video repository of many common human actions and show that a video matching the concept of the sketch is generally returned in one of the top three query results. © Springer-Verlag Berlin Heidelberg 2008.