Perceptual User Interfaces Logo
University of Stuttgart Logo

AutoBAP: Automatic Coding of Body Action and Posture Units from Wearable Sensors

Eduardo Velloso, Andreas Bulling, Hans Gellersen

Proc. Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII), pp. 135-140, 2013.


Abstract

Manual annotation of human body movement is an integral part of research on non-verbal communication and computational behaviour analysis but also a very time-consuming and tedious task. In this paper we present AutoBAP, a system that automates the coding of bodily expressions according to the body action and posture (BAP) coding scheme. Our system takes continuous body motion and gaze behaviour data as its input. The data is recorded using a full body motion tracking suit and a wearable eye tracker. From the data our system automatically generates a labelled XML file that can be visualised and edited with off-the-shelf video annotation tools. We evaluate our system in a laboratory-based user study with six participants performing scripted sequences of 184 actions. Results from the user study show that our prototype system is able to annotate 172 out of the 274 labels of the full BAP coding scheme with good agreement with a manual annotator (Cohen’s kappa > 0.6).

Links


BibTeX

@inproceedings{velloso13_acii, author = {Velloso, Eduardo and Bulling, Andreas and Gellersen, Hans}, title = {AutoBAP: Automatic Coding of Body Action and Posture Units from Wearable Sensors}, booktitle = {Proc. Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII)}, year = {2013}, pages = {135-140}, doi = {10.1109/ACII.2013.29} }