HistoryTracker: Minimizing human interactions in baseball game annotation

Jorge Piazentin Ono, Arvi Gjoka, Justin Salamon, Carlos Dietrich, Claudio T. Silva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The sport data tracking systems available today are based on specialized hardware (high-definition cameras, speed radars, RFID) to detect and track targets on the field. While effective, implementing and maintaining these systems pose a number of challenges, including high cost and need for close human monitoring. On the other hand, the sports analytics community has been exploring human computation and crowdsourcing in order to produce tracking data that is trustworthy, cheaper and more accessible. However, state-of-the-art methods require a large number of users to perform the annotation, or put too much burden into a single user. We propose HistoryTracker, a methodology that facilitates the creation of tracking data for baseball games by warm-starting the annotation process using a vast collection of historical data. We show that HistoryTracker helps users to produce tracking data in a fast and reliable way.

Original languageEnglish (US)
Title of host publicationCHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450359702
DOIs
StatePublished - May 2 2019
Event2019 CHI Conference on Human Factors in Computing Systems, CHI 2019 - Glasgow, United Kingdom
Duration: May 4 2019May 9 2019

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2019 CHI Conference on Human Factors in Computing Systems, CHI 2019
CountryUnited Kingdom
CityGlasgow
Period5/4/195/9/19

Keywords

  • Baseball
  • Hand annota
  • Sports analytics
  • Sports tracking

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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  • Cite this

    Ono, J. P., Gjoka, A., Salamon, J., Dietrich, C., & Silva, C. T. (2019). HistoryTracker: Minimizing human interactions in baseball game annotation. In CHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3290605.3300293