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Automatic Recognition of Playful Physical Activity Opportunities of the Urban Environment

Published: 07 September 2021 Publication History

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.

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  • (2022)Augmented Co-Design Methods for Climate Smart EnvironmentsHandbook of Research on Implementing Digital Reality and Interactive Technologies to Achieve Society 5.010.4018/978-1-6684-4854-0.ch008(156-183)Online publication date: 30-Jun-2022

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cover image ACM Other conferences
Academic Mindtrek '21: Proceedings of the 24th International Academic Mindtrek Conference
June 2021
229 pages
ISBN:9781450385145
DOI:10.1145/3464327
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 07 September 2021

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Author Tags

  1. computer vision
  2. machine learning
  3. parkour
  4. playable cities
  5. transfer learning
  6. urban design

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Mindtrek '21
Mindtrek '21: Academic Mindtrek 2021
June 1 - 3, 2021
Tampere/Virtual, Finland

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  • (2022)Augmented Co-Design Methods for Climate Smart EnvironmentsHandbook of Research on Implementing Digital Reality and Interactive Technologies to Achieve Society 5.010.4018/978-1-6684-4854-0.ch008(156-183)Online publication date: 30-Jun-2022

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