Authors:
Joachim Schmidt
1
and
Modesto Castrillón-Santana
2
Affiliations:
1
Bielefeld University, Technical Faculty, Applied Computer Science, Germany
;
2
Institute of Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Spain
Keyword(s):
Human robot interaction, face detection, model acquisition, automatic initialization, human body tracking.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Detecting 3D Objects Using Patterns of Motion and Appearance
;
Human-Computer Interaction
;
Methodologies and Methods
;
Model-Based Object Tracking in Image Sequences
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Retrieval of 3D Objects from Video Sequences
;
Tracking of People and Surveillance
Abstract:
Social robots require the ability to communicate and recognize the intention of a human interaction partner. Humans commonly make use of gestures for interactive purposes. For a social robot, recognition of gestures is therefore a necessary skill. As a common intermediate step, the pose of an individual is tracked over time making use of a body model. The acquisition of a suitable body model, i.e. self-starting the tracker, however, is a complex and challenging task. This paper presents an approach to facilitate the acquisition of the body model during interaction. Taking advantage of a robust face detection algorithm provides the opportunity for automatic and markerless acquisition of a 3D body model using a monocular color camera. For the given human robot interaction scenario, a prototype has been developed for a single user configuration. It provides automatic initialization and failure recovery of a 3D body tracker based on head and hand detection information, delivering promisi
ng results.
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