Home > Research > Publications & Outputs > Learning a human-perceived softness measure of ...

Research

Electronic data

  • LearningSoftnessMeasure_SAP

    Rights statement: © Owner/Author ACM, 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SAP '16 Proceedings of the ACM Symposium on Applied Perception http://dx.doi.org/10.1145/2931002.2931019

    Accepted author manuscript, 2.61 MB, PDF document

Links

Text available via DOI:

View graph of relations

Learning a human-perceived softness measure of virtual 3D objects

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Published

Standard

Learning a human-perceived softness measure of virtual 3D objects. / Lau, Manfred; Dev, Kapil; Dorsey, Julie et al.
SAP '16 Proceedings of the ACM Symposium on Applied Perception. New York: ACM, 2016. p. 65-68.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Lau, M, Dev, K, Dorsey, J & Rushmeier, H 2016, Learning a human-perceived softness measure of virtual 3D objects. in SAP '16 Proceedings of the ACM Symposium on Applied Perception. ACM, New York, pp. 65-68, ACM Symposium on Applied Perception, Anaheim, California, United States, 22/07/16. https://doi.org/10.1145/2931002.2931019

APA

Lau, M., Dev, K., Dorsey, J., & Rushmeier, H. (2016). Learning a human-perceived softness measure of virtual 3D objects. In SAP '16 Proceedings of the ACM Symposium on Applied Perception (pp. 65-68). ACM. https://doi.org/10.1145/2931002.2931019

Vancouver

Lau M, Dev K, Dorsey J, Rushmeier H. Learning a human-perceived softness measure of virtual 3D objects. In SAP '16 Proceedings of the ACM Symposium on Applied Perception. New York: ACM. 2016. p. 65-68 doi: 10.1145/2931002.2931019

Author

Lau, Manfred ; Dev, Kapil ; Dorsey, Julie et al. / Learning a human-perceived softness measure of virtual 3D objects. SAP '16 Proceedings of the ACM Symposium on Applied Perception. New York : ACM, 2016. pp. 65-68

Bibtex

@inproceedings{effce95e583b496cb0a24b2bf09235f9,
title = "Learning a human-perceived softness measure of virtual 3D objects",
abstract = "We introduce the problem of computing a human-perceived softness measure for virtual 3D objects. As the virtual objects do not exist in the real world, we do not directly consider their physical properties but instead compute the human-perceived softness of the geometric shapes. We collect crowdsourced data where humans rank their perception of the softness of vertex pairs on virtual 3D models. We then compute shape descriptors and use a learning to-rank approach to learn a softness measure mapping any vertex to a softness value. Finally, we demonstrate our framework with a variety of 3D shapes.",
author = "Manfred Lau and Kapil Dev and Julie Dorsey and Holly Rushmeier",
note = "{\textcopyright} Owner/Author ACM, 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SAP '16 Proceedings of the ACM Symposium on Applied Perception http://dx.doi.org/10.1145/2931002.2931019; ACM Symposium on Applied Perception ; Conference date: 22-07-2016 Through 23-07-2016",
year = "2016",
month = jul,
day = "22",
doi = "10.1145/2931002.2931019",
language = "English",
isbn = "9781450343831",
pages = "65--68",
booktitle = "SAP '16 Proceedings of the ACM Symposium on Applied Perception",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Learning a human-perceived softness measure of virtual 3D objects

AU - Lau, Manfred

AU - Dev, Kapil

AU - Dorsey, Julie

AU - Rushmeier, Holly

N1 - © Owner/Author ACM, 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SAP '16 Proceedings of the ACM Symposium on Applied Perception http://dx.doi.org/10.1145/2931002.2931019

PY - 2016/7/22

Y1 - 2016/7/22

N2 - We introduce the problem of computing a human-perceived softness measure for virtual 3D objects. As the virtual objects do not exist in the real world, we do not directly consider their physical properties but instead compute the human-perceived softness of the geometric shapes. We collect crowdsourced data where humans rank their perception of the softness of vertex pairs on virtual 3D models. We then compute shape descriptors and use a learning to-rank approach to learn a softness measure mapping any vertex to a softness value. Finally, we demonstrate our framework with a variety of 3D shapes.

AB - We introduce the problem of computing a human-perceived softness measure for virtual 3D objects. As the virtual objects do not exist in the real world, we do not directly consider their physical properties but instead compute the human-perceived softness of the geometric shapes. We collect crowdsourced data where humans rank their perception of the softness of vertex pairs on virtual 3D models. We then compute shape descriptors and use a learning to-rank approach to learn a softness measure mapping any vertex to a softness value. Finally, we demonstrate our framework with a variety of 3D shapes.

U2 - 10.1145/2931002.2931019

DO - 10.1145/2931002.2931019

M3 - Conference contribution/Paper

SN - 9781450343831

SP - 65

EP - 68

BT - SAP '16 Proceedings of the ACM Symposium on Applied Perception

PB - ACM

CY - New York

T2 - ACM Symposium on Applied Perception

Y2 - 22 July 2016 through 23 July 2016

ER -