SHL Activity Recognition Challenge @HASCA/Ubicomp 2020 (third edition)

[Daniel Roggen]

Dear colleagues,

The Wearable Technologies Lab at the University of Sussex is glad to inform you
about the third SHL Activity Recognition Challenge
(http://www.shl-dataset.org/activity-recognition-challenge-2020/).

This follows on our very successful 2018 and 2019 challenges, which saw the
participation of more than 40 teams.

This 2020 edition focuses on recognising 8 modes of locomotion and transportation
(activities) in a user-independent manner with an unknown phone position. The
goal is to recognize the user activity from data coming from the phone of a test
user. The location of that phone is not specified. Training data is provided for
a train user, with all the 4 phone positions available. One of these position will
be identical to that of the test user.

The dataset used for this challenge comprises 59 days of training data, 6 days
of validation data, and 40 days of test data.

The participants will have to develop an algorithm pipeline that will process the
sensor data, create models and output the recognized activities.

All teams will receive a certificate of participation, and the best three teams
will also receive a prize (800£, 400£ and 200£)!

The participants should also write a technical paper explaining their methods
and development process, which will be presented at a special session at the
HASCA Workshop at Ubicomp 2020 (http://hasca2020.hasc.jp/), and included in the
adjunct proceedings.


The timeline of the challenge:

- Registration via email: as soon as possible, but not later than 15.04.2020
- Challenge duration: 05.04.2020 – 15.06.2020
- Submission of predictions deadline: 15.06.2020
- HASCA paper submission: 19.06.2020
- HASCA Workshop presentation: 12. or 13.09.2020 in Cancun, Mexico @UbiComp/ISWC conference


Organizers:
- Prof. Daniel Roggen, University of Sussex (UK)
- Prof. Hristijan Gjoreski, Ss. Cyril and Methodius University (MK)
- Dr. Lin Wang, Queen Mary University of London (UK)
- Mathias Ciliberto, University of Sussex (UK)
- Dr. Kazuya Murao, Ritsumeikan University (JP)
- Dr. Tsuyoshi Okita, Kyushu Institute of Technology (JP)
- Paula Lago, Kyushu Institute of Technology  (JP)

Contact:
All inquiries should be directed to: shldataset...@gmail.com