ChallengeUP 2019 : Challenge UP 2019: Multimodal Fall Detection [ML competition @ IEEE IJCNN 2019]
Call For Papers
We are very much delighted to invite you to participate in the Challenge UP 2019: Multimodal Fall Detection competition in the upcoming International Joint Conference on Neural Networks (IJCNN 2019), during July 14-19 at Budapest, Hungary.
Challenge UP 2019: Multimodal Fall Detection is a competition focused on the recognition of a range of five falls and six daily activities, performed by 12 subjects, three attempts each. Data were collected from five wearable sensors, one headset, six ambient infrared sensors and two cameras, containing more than 150GB of information.
Participants can compete as individual or team. During the training phase, the training dataset will be exposed (nine subjects and labeled data) and participants can explore different strategies for classification of the falls/activities. After that, during the testing phase, the testing dataset will be exposed (three new subjects and no labeled data) and participants compute estimated classification of the falls/activities. For final submissions, participants must prepare a CSV file with the final estimations and a report paper (limited to 6-8 pages) containing at least the methodology, results and conclusions.
All the information about the competition, datasets, rules, important dates and registration can be found in the following link:
- December 3, 2018 – Open registration
- December 10, 2018 – Publication of the training set
- March 25, 2019 – Publication of the testing set
- April 26, 2019 – Deadline for results submission (CSV file) and close registration
- May 17, 2019 – Deadline for paper submission
- June 28, 2019 – Notification of results
- July 14-19, 2019 – Awarding during IJCNN 2019
1st Place - Drone Parrot Bebop 2 FPV
2nd Place - Apple TV 4K
3rd Place - Google Home
The three best submissions will be awarded, and the winner will be invited to submit an extended paper to the Special Issue on Artificial Intelligence in Multimodal Sensors for Healthcare in the Journal of Sensors – Hindawi (IF 2.057).
In addition, all submitted papers will be considered for publication in an edited book entitled “Challenges and Trends in Multimodal Fall Detection for Healthcare” to be tentatively appeared on the Cognitive Technologies series in Springer.
Thank you for your time and looking forward to your participation.
If you have any questions, do not hesitate to contact us.
More information about IJCNN 2019:
Hiram Ponce, email@example.com
Lourdes Martínez-Villaseñor, firstname.lastname@example.org
León Palafox, email@example.com
Karina Pérez-Daniel, firstname.lastname@example.org
Faculty of Engineering, Universidad Panamericana,
Mexico City 03920, Mexico