Toward computer vision systems that understand real-world assembly processes

Jonathan D. Jones, Gregory D. Hager, Sanjeev Khudanpur

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

Abstract

Many applications of computer vision require robust systems that can parse complex structures as they evolve in time. Using a block construction task as a case study, we illustrate the main components involved in building such systems. We evaluate performance at three increasingly-detailed levels of spatial granularity on two multimodal (RGBD + IMU) datasets. On the first, designed to match the assumptions of the model, we report better than 90% accuracy at the finest level of granularity. On the second, designed to test the robustness of our model under adverse, real-world conditions, we report 67% accuracy and 91% precision at the mid-level of granularity. We show that this seemingly simple process presents many opportunities to expand the frontiers of computer vision and action recognition.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages426-434
Number of pages9
ISBN (Electronic)9781728119755
DOIs
StatePublished - Mar 4 2019
Event19th IEEE Winter Conference on Applications of Computer Vision, WACV 2019 - Waikoloa Village, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameProceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019

Conference

Conference19th IEEE Winter Conference on Applications of Computer Vision, WACV 2019
CountryUnited States
CityWaikoloa Village
Period1/7/191/11/19

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Jones, J. D., Hager, G. D., & Khudanpur, S. (2019). Toward computer vision systems that understand real-world assembly processes. In Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019 (pp. 426-434). [8659114] (Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WACV.2019.00051