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Detecting Common Human Actions in Video by Sketching
Project Summary:
We present a method for detecting common human actions in video, common to athletics and surveillance, using intuitive sketches and motion cues. This framework 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 have applied our method to a publicly available video repository of many common human actions and showed that a video matching the concept of the sketch is generally returned in one of the top three query results.We are currently in the process of extending the graphical user interface, and we plan to conduct a user study to evaluate the usability of the system and intuitiveness of sketch input.
Publications:
E. Suma, C.W. Sinclair, J. Babbs, and R. Souvenir, "A Sketch-Based Approach for Detecting Common Human Actions," International Symposium on Visual Computing 2008, pp. 418-427(30% acceptance rate). PDF