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Cited by 344

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Panoptic Studio: A Massively Multiview System for Social Interaction Capture

Open access
Joo, Hanbyul, Simon, Tomas, Li, Xulong, Liu, Hao, Tan, Lei, Gui, Lin, Banerjee, Sean, Godisart, Timothy, Nabbe, Bart, Matthews, Iain, Kanade, Takeo, Nobuhara, Shohei, Sheikh, Yaser·2019·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

We present an approach to capture the 3D motion of a group of people engaged in a social interaction. The core challenges in capturing social interactions are: (1) occlusion is functional and frequent; (2) subtle motion needs to be measured over a space large enough to host a social group; (3) human appearance and configuration variation is immense; and (4) attaching markers to the body may prime the nature of interactions. The Panoptic Studio is a system organized around the thesis that social interactions should be measured through the integration of perceptual analyses over a large variety of view points. We present a modularized system designed around this principle, consisting of integrated structural, hardware, and software innovations. The system takes, as input, 480 synchronized video streams of multiple people engaged in social activities, and produces, as output, the labeled time-varying 3D structure of anatomical landmarks on individuals in the space. Our algorithm is designed to fuse the "weak" perceptual processes in the large number of views by progressively generating skeletal proposals from low-level appearance cues, and a framework for temporal refinement is also presented by associating body parts to reconstructed dense 3D trajectory stream. Our system and method are the first in reconstructing full body motion of more than five people engaged in social interactions without using markers. We also empirically demonstrate the impact of the number of views in achieving this goal.

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Metadata

Authors
Joo, H., Simon, T., Li, X., Liu, H., Tan, L., Gui, L., Banerjee, S., Godisart, T., Nabbe, B., Matthews, I., Kanade, T., Nobuhara, S., & Sheikh, Y.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
2019-01-01
Volume
41
Issue
1
Pages
190-204
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
  • 1939-3539
OpenAlex
W2771965516
Cited by
344
References
2
FWCI
9.21
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Panoptic Studio: A Massively Multiview System for Social Interaction Capture. https://app.cochat.ai/papers/10.1109/tpami.2017.2782743
The paper
Joo, H., Simon, T., Li, X., Liu, H., Tan, L., Gui, L., Banerjee, S., Godisart, T., Nabbe, B., Matthews, I., Kanade, T., Nobuhara, S., & Sheikh, Y. (2019). Panoptic Studio: A Massively Multiview System for Social Interaction Capture. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2017.2782743

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