Authors:
Jan Baumann
;
Raoul Wessel
;
Björn Krüger
and
Andreas Weber
Affiliation:
University of Bonn, Germany
Keyword(s):
Animation, Action Recognition, Accelerometer, Motion Capture.
Related
Ontology
Subjects/Areas/Topics:
Animation Algorithms and Techniques
;
Animation and Simulation
;
Animation from Motion Capture
;
Computer Vision, Visualization and Computer Graphics
Abstract:
This work presents a novel and generic data-driven method for recognizing human full body actions from live motion data originating from various sources. The method queries an annotated motion capture database for similar motion segments, capable to handle temporal deviations from the original motion. The approach is online-capable, works in realtime, requires virtually no preprocessing and is shown to work with a variety of feature sets extracted from input data including positional data, sparse accelerometer signals, skeletons extracted from depth sensors and even video data. Evaluation is done by comparing against a frame-based Support Vector Machine approach on a freely available motion capture database as well as a database containing Judo referee signal motions and concludes by demonstrating the applicability of the method in a vision-based scenario using video data.