Automatic Recognition of Playful Physical Activity Opportunities of the Urban Environment

Tuure Saloheimo, Maximus Kaos, Pia Fricker, Perttu Hämäläinen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)
283 Downloads (Pure)

Abstract

We investigate deep neural networks in recognizing playful physical activity opportunities of the urban environment. Using transfer learning with a pre-trained Faster R-CNN network, we are able to train a parkour training spot detector with only a few thousand street level photographs. We utilize a simple and efficient annotation scheme that only required a few days of annotation work by parkour hobbyists, and should be easily applicable in other contexts, e.g. skateboarding. The technology is tested through parkour spot exploration and visualization experiments. To inform and motivate the technology development, we also conducted an interview study about what makes an interesting parkour spot and how parkour hobbyists find spots. Our work should be valuable for researchers and practitioners of fields like urban design and exercise video games, e.g., by providing data for a location-based game akin to
Pokémon Go, but with parkour-themed gameplay and challenges.
Original languageEnglish
Title of host publicationAcademic Mindtrek 2021
Subtitle of host publicationProceedings of the 24th International Conference on Academic Mindtrek
PublisherACM
Pages49-59
Number of pages11
ISBN (Print)978-1-4503-8514-5
DOIs
Publication statusPublished - 1 Jun 2021
MoE publication typeA4 Conference publication
EventMindTrek Conference - Online, Tampere, Finland
Duration: 1 Jun 20213 Jun 2021
Conference number: 24
https://www.mindtrek.org/2021
https://www.mindtrek.org/2021/academic/

Conference

ConferenceMindTrek Conference
Country/TerritoryFinland
CityTampere
Period01/06/202103/06/2021
Internet address

Keywords

  • machine learning
  • parkour
  • transfer learning
  • computer vision
  • urban design
  • playable cities

Fingerprint

Dive into the research topics of 'Automatic Recognition of Playful Physical Activity Opportunities of the Urban Environment'. Together they form a unique fingerprint.

Cite this