Collection of visual data in climbing experiments for addressing the role of multi-modal exploration in motor learning efficiency

Adam Schmidt*, Dominic Orth, Ludovic Seifert

*Corresponding author for this work

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

Abstract

Understanding how skilled performance in human endeavor is acquired through practice has benefited markedly from technologies that can track movements of the limb, body and eyes with reference to the environment. A significant challenge within this context is to develop time efficient methods for observing multiple levels of motor system activity throughout practice. Whilst, activity can be recorded using video based systems, crossing multiple levels of analysis is a substantive problematic within the computer vision and human movement domains. The goal of this work is to develop a registration system to collect movement activity in an environment typical to those that individuals normally seek to participate (sports and physical activities). Detailed are the registration system and procedure to collect data necessary for studying skill acquisition processes during difficult indoor climbing tasks, practiced by skilled climbers. Of particular interest are the problems addressed in trajectory reconstruction when faced with limitations of the registration process and equipment in such unconstrained setups. These include: abrupt movements that violate the common assumption of the smoothness of the camera trajectory; significant motion blur and rolling shutter effects; highly repetitive environment consisting of many similar objects.

Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems - 17th International Conference, ACIVS 2016, Proceedings
PublisherSpringer/Verlag
Pages674-684
Number of pages11
Volume10016 LNCS
ISBN (Print)9783319486796
DOIs
Publication statusPublished - 2016
Event17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016 - Lecce, Italy
Duration: 24 Oct 201627 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10016 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016
Country/TerritoryItaly
CityLecce
Period24/10/1627/10/16

Keywords

  • Data collection
  • Gaze tracking
  • Motor learning
  • Registration system
  • Rock climbing
  • Visual scene understanding

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