Automatic Reasoning about Causal Events in Surveillance Video. (7th February 2011)

• Record Type: Journal Article
• Authors: Robertson Robertson, Neil M. Neil M.; Reid Reid, Ian D. Ian D.
• Other Names: Di Stefano Di Stefano Luigi Luigi Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2011(2011)
• Publication Date: 2011-02-07
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2011/530325
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : We present a new method for explaining causal interactions among people in video. The input to the overall system is video in which people are low/medium resolution. We extract and maintain a set of qualitative descriptions of single-person activity using the low-level vision techniques of spatiotemporal action recognition and gaze-direction approximation. This models the input to the "sensors" of the person agent in the scene and is a general sensing strategy for a person agent in a variety of application domains. The information subsequently available to the reasoning process is deliberately limited to model what an agent would actually be able to sense. The reasoning is therefore not a classical "all-knowing" strategy but uses these "sensed" facts obtained from the agents, combined with generic domain knowledge, to generate causal explanations of interactions. We present results from urban surveillance video.