TY - GEN
T1 - Panel
T2 - Workshops held at the 16th European Conference on Computer Vision, ECCV 2020
AU - Wang, James Z.
AU - Badler, Norman
AU - Berthouze, Nadia
AU - Gilmore, Rick O.
AU - Johnson, Kerri L.
AU - Lapedriza, Agata
AU - Lu, Xin
AU - Troje, Nikolaus
N1 - Funding Information:
Kerri L. Johnson: One of the challenges for this research is that for many researchers, particularly those who are not at R1 universities1, the necessary equipment is cost and space prohibitive. Without sizable funding through either equipment grants or start-up funds, many simply cannot conduct research in this area. This makes the publication of open databases of body movements, both in raw and visual formats, all the more important. Unfortunately, many of the existing stimulus archives are insufficient for answering anything but very narrow questions. Expanding those archives to include more variety of movements and more diversity of individuals will expand the research questions that can be probed.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Developing computational methods for bodily expressed emotion understanding can benefit from knowledge and approaches of multiple fields, including computer vision, robotics, psychology/psychiatry, graphics, data mining, machine learning, and movement analysis. The panel, consisting of active researchers in some closely-related fields, attempts to open a discussion on the future of this new and exciting research area. This paper documents the opinions expressed by the individual panelists.
AB - Developing computational methods for bodily expressed emotion understanding can benefit from knowledge and approaches of multiple fields, including computer vision, robotics, psychology/psychiatry, graphics, data mining, machine learning, and movement analysis. The panel, consisting of active researchers in some closely-related fields, attempts to open a discussion on the future of this new and exciting research area. This paper documents the opinions expressed by the individual panelists.
UR - http://www.scopus.com/inward/record.url?scp=85101387991&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85101387991&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-66415-2_51
DO - 10.1007/978-3-030-66415-2_51
M3 - Conference contribution
AN - SCOPUS:85101387991
SN - 9783030664145
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 733
EP - 746
BT - Computer Vision – ECCV 2020 Workshops, Proceedings
A2 - Bartoli, Adrien
A2 - Fusiello, Andrea
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 23 August 2020 through 28 August 2020
ER -