Integrated vision system for the semantic interpretation of activities where a person handles objects

Authors:
Markus Vincze;Michael Zillich;Wolfgang Ponweiser;Vaclav Hlavac;Jiri Matas;Stepan Obdrzalek;Hilary Buxton;Jonathan Howell;Kingsley Sage;Antonis Argyros;Christoph Eberst;Gerald Umgeher
Affiliations:
Automation and Control Institute, Vienna University of Technology, Vienna, Austria;Automation and Control Institute, Vienna University of Technology, Vienna, Austria;Automation and Control Institute, Vienna University of Technology, Vienna, Austria;Center for Machine Perception, Czech Technical University, Prague, Czech Republic;Center for Machine Perception, Czech Technical University, Prague, Czech Republic;Center for Machine Perception, Czech Technical University, Prague, Czech Republic;School of Cognitive and Computing Sciences, University of Sussex, Brighton, UK;School of Cognitive and Computing Sciences, University of Sussex, Brighton, UK;School of Cognitive and Computing Sciences, University of Sussex, Brighton, UK;Computer Vision and Robotics Laboratory, Foundation for Research and Technology Hellas (FORTH), Heraklion, Greece;PROFACTOR Produktionsforschungs GmbH, Steyr, Austria;PROFACTOR Produktionsforschungs GmbH, Steyr, Austria
Venue:
Computer Vision and Image Understanding
Year:
2009

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Abstract

Interpretation of human activity is primarily known from surveillance and video analysis tasks and concerned with the persons alone. In this paper we present an integrated system that gives a natural language interpretation of activities where a person handles objects. The system integrates low-level image components such as hand and object tracking, detection and recognition, with high-level processes such as spatio-temporal object relationship generation, posture and gesture recognition, and activity reasoning. A task-oriented approach focuses processing to achieve near real-time and to react depending on the situation context.