Workshop and Challenge on Robust activity recognition

Call for Participation

Robust machine learning techniques for human activity recognition
A full day workshop at the IEEE conf on Systems, Man and Cybernetics 2011
October 9-12, Anchorage, USA

Human activity recognition can be used to devise assistants that
provide proactive support by exploiting the knowledge of the user’s
context, determined from sensors located on-body. The design and
development of these systems pose important challenges to the machine
learning community as they typically involve high-dimensional,
multimodal streams of data characterised by a large variability; where
data portions may be missing or labels can be unreliable.

Notwithstanding the large amount of research endeavours aimed at
tackling these issues, the comparison of different approaches is often
not possible due to the lack of common benchmarking tools and datasets
that allow for replicable and fair testing procedures across several
research groups. The aim of this workshop is to discuss and compare
different methods for robust activity recognition, as well as putting
forward the need for common resources for such comparison. To promote
such comparison, the workshop is associated to an activity recognition
challenge (see below) where contributed methods will be evaluated on a
benchmark database of daily activities recorded using a multimodal
network of on-body sensors.

Invited Speakers
Prof. Dr. Paul Lukowicz, Universität Passau
Dr. Thomas Ploetz, Newcastle University

Important dates
June 28, 2011: Submission deadline
July 1, 2011: Acceptance/rejection notification
July 5, 2011: Camera ready due
October 9, 2011: Workshop

Contact: activityrecognition.challenge(at)

Activity recognition Challenge

As mentioned above, there are established benchmarking problems for
activity recognition. We intend to address this issue by setting up a
challenge on activity recognition addressing key questions in
activity recognition such as classification based on multimodal
recordings, activity spotting and robustness to noise. To this end we
provide a benchmark database of daily activities recorded in a sensor
rich environment.

Prizes will be awarded to participants that achieve the best
performance, and the overall lessons and results obtained from this
challenge will be presented at the associated workshop at the IEEE
Conference on Systems, Man and Cybernetics 2011. Moreover, we are
currently arranging the future publication of selected contributions in
a top journal in the field.

Challenge description:

Contact: activityrecognition.challenge(at)

Important dates
September 9, 2011: Final submission date
October 9, 2011: Final results and conclusions presented at the SMC workshop

Ricardo Chavarriaga, EPFL, Switzerland
Daniel Roggen, ETHZ, Switzerland
Alois Ferscha, Johannes Kepler University, Linz, Austria
Paul Lukowicz, U. Passau, Germany

Activity and Context Recognition with
Opportunistic Sensor Configurations