AutoViDev

A Computer-Vision Framework to Enhance and Accelerate Research in Human Development

Ori Ossmy, Rick Owen Gilmore, Karen E. Adolph

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

Abstract

Interdisciplinary exchange of ideas and tools can accelerate scientific progress. For example, findings from developmental and vision science have spurred recent advances in artificial intelligence and computer vision. However, relatively little attention has been paid to how artificial intelligence and computer vision can facilitate research in developmental science. The current study presents AutoViDev—an automatic video-analysis tool that uses machine learning and computer vision to support video-based developmental research. AutoViDev identifies full body position estimations in real-time video streams using convolutional pose machine-learning algorithms. AutoViDev provides valuable information about a variety of behaviors, including gaze direction, facial expressions, posture, locomotion, manual actions, and interactions with objects. We present a high-level architecture of the framework and describe two projects that demonstrate its usability. We discuss the benefits of applying AutoViDev to large-scale, shared video datasets and highlight how machine learning and computer vision can enhance and accelerate research in developmental science.

Original languageEnglish (US)
Title of host publicationAdvances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC
EditorsSupriya Kapoor, Kohei Arai
PublisherSpringer Verlag
Pages147-156
Number of pages10
ISBN (Print)9783030177973
DOIs
StatePublished - Jan 1 2020
EventComputer Vision Conference, CVC 2019 - Las Vegas, United States
Duration: Apr 25 2019Apr 26 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume944
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceComputer Vision Conference, CVC 2019
CountryUnited States
CityLas Vegas
Period4/25/194/26/19

Fingerprint

Computer vision
Learning systems
Artificial intelligence
Learning algorithms

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Ossmy, O., Gilmore, R. O., & Adolph, K. E. (2020). AutoViDev: A Computer-Vision Framework to Enhance and Accelerate Research in Human Development. In S. Kapoor, & K. Arai (Eds.), Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC (pp. 147-156). (Advances in Intelligent Systems and Computing; Vol. 944). Springer Verlag. https://doi.org/10.1007/978-3-030-17798-0_14
Ossmy, Ori ; Gilmore, Rick Owen ; Adolph, Karen E. / AutoViDev : A Computer-Vision Framework to Enhance and Accelerate Research in Human Development. Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC. editor / Supriya Kapoor ; Kohei Arai. Springer Verlag, 2020. pp. 147-156 (Advances in Intelligent Systems and Computing).
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Ossmy, O, Gilmore, RO & Adolph, KE 2020, AutoViDev: A Computer-Vision Framework to Enhance and Accelerate Research in Human Development. in S Kapoor & K Arai (eds), Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC. Advances in Intelligent Systems and Computing, vol. 944, Springer Verlag, pp. 147-156, Computer Vision Conference, CVC 2019, Las Vegas, United States, 4/25/19. https://doi.org/10.1007/978-3-030-17798-0_14

AutoViDev : A Computer-Vision Framework to Enhance and Accelerate Research in Human Development. / Ossmy, Ori; Gilmore, Rick Owen; Adolph, Karen E.

Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC. ed. / Supriya Kapoor; Kohei Arai. Springer Verlag, 2020. p. 147-156 (Advances in Intelligent Systems and Computing; Vol. 944).

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

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Ossmy O, Gilmore RO, Adolph KE. AutoViDev: A Computer-Vision Framework to Enhance and Accelerate Research in Human Development. In Kapoor S, Arai K, editors, Advances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC. Springer Verlag. 2020. p. 147-156. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-17798-0_14