---
_id: '670'
abstract:
- lang: eng
text: We propose an efficient method to model paper tearing in the context of interactive
modeling. The method uses geometrical information to automatically detect potential
starting points of tears. We further introduce a new hybrid geometrical and physical-based
method to compute the trajectory of tears while procedurally synthesizing high
resolution details of the tearing path using a texture based approach. The results
obtained are compared with real paper and with previous studies on the expected
geometric paths of paper that tears.
article_processing_charge: No
article_type: original
author:
- first_name: Camille
full_name: Schreck, Camille
id: 2B14B676-F248-11E8-B48F-1D18A9856A87
last_name: Schreck
- first_name: Damien
full_name: Rohmer, Damien
last_name: Rohmer
- first_name: Stefanie
full_name: Hahmann, Stefanie
last_name: Hahmann
citation:
ama: Schreck C, Rohmer D, Hahmann S. Interactive paper tearing. Computer Graphics
Forum. 2017;36(2):95-106. doi:10.1111/cgf.13110
apa: Schreck, C., Rohmer, D., & Hahmann, S. (2017). Interactive paper tearing.
Computer Graphics Forum. Wiley. https://doi.org/10.1111/cgf.13110
chicago: Schreck, Camille, Damien Rohmer, and Stefanie Hahmann. “Interactive Paper
Tearing.” Computer Graphics Forum. Wiley, 2017. https://doi.org/10.1111/cgf.13110.
ieee: C. Schreck, D. Rohmer, and S. Hahmann, “Interactive paper tearing,” Computer
Graphics Forum, vol. 36, no. 2. Wiley, pp. 95–106, 2017.
ista: Schreck C, Rohmer D, Hahmann S. 2017. Interactive paper tearing. Computer
Graphics Forum. 36(2), 95–106.
mla: Schreck, Camille, et al. “Interactive Paper Tearing.” Computer Graphics
Forum, vol. 36, no. 2, Wiley, 2017, pp. 95–106, doi:10.1111/cgf.13110.
short: C. Schreck, D. Rohmer, S. Hahmann, Computer Graphics Forum 36 (2017) 95–106.
date_created: 2018-12-11T11:47:49Z
date_published: 2017-05-01T00:00:00Z
date_updated: 2021-01-12T08:08:37Z
day: '01'
ddc:
- '000'
department:
- _id: ChWo
doi: 10.1111/cgf.13110
intvolume: ' 36'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://hal.inria.fr/hal-01647113/file/eg_2017_schreck_paper_tearing.pdf
month: '05'
oa: 1
oa_version: Published Version
page: 95 - 106
project:
- _id: 25357BD2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 24352-N23
name: 'Deep Pictures: Creating Visual and Haptic Vector Images'
publication: Computer Graphics Forum
publication_identifier:
issn:
- '01677055'
publication_status: published
publisher: Wiley
publist_id: '7056'
quality_controlled: '1'
scopus_import: 1
status: public
title: Interactive paper tearing
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2017'
...
---
_id: '1367'
abstract:
- lang: eng
text: One of the major challenges in physically based modelling is making simulations
efficient. Adaptive models provide an essential solution to these efficiency goals.
These models are able to self-adapt in space and time, attempting to provide the
best possible compromise between accuracy and speed. This survey reviews the adaptive
solutions proposed so far in computer graphics. Models are classified according
to the strategy they use for adaptation, from time-stepping and freezing techniques
to geometric adaptivity in the form of structured grids, meshes and particles.
Applications range from fluids, through deformable bodies, to articulated solids.
acknowledgement: This work was partly supported by the starting grants ADAPT and BigSplash,
as well as the advanced grant EXPRESSIVE from the European Research Council (ERC-2012-StG_20111012,
ERC-2014-StG_638176 and ERC-2011-ADG_20110209).
article_processing_charge: No
author:
- first_name: Pierre
full_name: Manteaux, Pierre
last_name: Manteaux
- first_name: Christopher J
full_name: Wojtan, Christopher J
id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87
last_name: Wojtan
orcid: 0000-0001-6646-5546
- first_name: Rahul
full_name: Narain, Rahul
last_name: Narain
- first_name: Stéphane
full_name: Redon, Stéphane
last_name: Redon
- first_name: François
full_name: Faure, François
last_name: Faure
- first_name: Marie
full_name: Cani, Marie
last_name: Cani
citation:
ama: Manteaux P, Wojtan C, Narain R, Redon S, Faure F, Cani M. Adaptive physically
based models in computer graphics. Computer Graphics Forum. 2017;36(6):312-337.
doi:10.1111/cgf.12941
apa: Manteaux, P., Wojtan, C., Narain, R., Redon, S., Faure, F., & Cani, M.
(2017). Adaptive physically based models in computer graphics. Computer Graphics
Forum. Wiley-Blackwell. https://doi.org/10.1111/cgf.12941
chicago: Manteaux, Pierre, Chris Wojtan, Rahul Narain, Stéphane Redon, François
Faure, and Marie Cani. “Adaptive Physically Based Models in Computer Graphics.”
Computer Graphics Forum. Wiley-Blackwell, 2017. https://doi.org/10.1111/cgf.12941.
ieee: P. Manteaux, C. Wojtan, R. Narain, S. Redon, F. Faure, and M. Cani, “Adaptive
physically based models in computer graphics,” Computer Graphics Forum,
vol. 36, no. 6. Wiley-Blackwell, pp. 312–337, 2017.
ista: Manteaux P, Wojtan C, Narain R, Redon S, Faure F, Cani M. 2017. Adaptive physically
based models in computer graphics. Computer Graphics Forum. 36(6), 312–337.
mla: Manteaux, Pierre, et al. “Adaptive Physically Based Models in Computer Graphics.”
Computer Graphics Forum, vol. 36, no. 6, Wiley-Blackwell, 2017, pp. 312–37,
doi:10.1111/cgf.12941.
short: P. Manteaux, C. Wojtan, R. Narain, S. Redon, F. Faure, M. Cani, Computer
Graphics Forum 36 (2017) 312–337.
date_created: 2018-12-11T11:51:37Z
date_published: 2017-09-01T00:00:00Z
date_updated: 2023-09-20T11:05:36Z
day: '01'
ddc:
- '000'
department:
- _id: ChWo
doi: 10.1111/cgf.12941
external_id:
isi:
- '000408634200019'
file:
- access_level: open_access
checksum: 7676e9a9ead6d58c3000988c97deb2ef
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:21Z
date_updated: 2020-07-14T12:44:47Z
file_id: '5208'
file_name: IST-2016-634-v1+1_starAdaptivity-cgf.pdf
file_size: 1434439
relation: main_file
file_date_updated: 2020-07-14T12:44:47Z
has_accepted_license: '1'
intvolume: ' 36'
isi: 1
issue: '6'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Submitted Version
page: 312 - 337
publication: Computer Graphics Forum
publication_identifier:
issn:
- '01677055'
publication_status: published
publisher: Wiley-Blackwell
publist_id: '5873'
pubrep_id: '634'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Adaptive physically based models in computer graphics
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 36
year: '2017'
...
---
_id: '1152'
abstract:
- lang: eng
text: We propose a new memetic strategy that can solve the multi-physics, complex
inverse problems, formulated as the multi-objective optimization ones, in which
objectives are misfits between the measured and simulated states of various governing
processes. The multi-deme structure of the strategy allows for both, intensive,
relatively cheap exploration with a moderate accuracy and more accurate search
many regions of Pareto set in parallel. The special type of selection operator
prefers the coherent alternative solutions, eliminating artifacts appearing in
the particular processes. The additional accuracy increment is obtained by the
parallel convex searches applied to the local scalarizations of the misfit vector.
The strategy is dedicated for solving ill-conditioned problems, for which inverting
the single physical process can lead to the ambiguous results. The skill of the
selection in artifact elimination is shown on the benchmark problem, while the
whole strategy was applied for identification of oil deposits, where the misfits
are related to various frequencies of the magnetic and electric waves of the magnetotelluric
measurements. 2016 Elsevier B.V.
article_processing_charge: No
author:
- first_name: Ewa P
full_name: Gajda-Zagorska, Ewa P
id: 47794CF0-F248-11E8-B48F-1D18A9856A87
last_name: Gajda-Zagorska
- first_name: Robert
full_name: Schaefer, Robert
last_name: Schaefer
- first_name: Maciej
full_name: Smołka, Maciej
last_name: Smołka
- first_name: David
full_name: Pardo, David
last_name: Pardo
- first_name: Julen
full_name: Alvarez Aramberri, Julen
last_name: Alvarez Aramberri
citation:
ama: Gajda-Zagorska EP, Schaefer R, Smołka M, Pardo D, Alvarez Aramberri J. A multi
objective memetic inverse solver reinforced by local optimization methods. Journal
of Computational Science. 2017;18:85-94. doi:10.1016/j.jocs.2016.06.007
apa: Gajda-Zagorska, E. P., Schaefer, R., Smołka, M., Pardo, D., & Alvarez Aramberri,
J. (2017). A multi objective memetic inverse solver reinforced by local optimization
methods. Journal of Computational Science. Elsevier. https://doi.org/10.1016/j.jocs.2016.06.007
chicago: Gajda-Zagorska, Ewa P, Robert Schaefer, Maciej Smołka, David Pardo, and
Julen Alvarez Aramberri. “A Multi Objective Memetic Inverse Solver Reinforced
by Local Optimization Methods.” Journal of Computational Science. Elsevier,
2017. https://doi.org/10.1016/j.jocs.2016.06.007.
ieee: E. P. Gajda-Zagorska, R. Schaefer, M. Smołka, D. Pardo, and J. Alvarez Aramberri,
“A multi objective memetic inverse solver reinforced by local optimization methods,”
Journal of Computational Science, vol. 18. Elsevier, pp. 85–94, 2017.
ista: Gajda-Zagorska EP, Schaefer R, Smołka M, Pardo D, Alvarez Aramberri J. 2017.
A multi objective memetic inverse solver reinforced by local optimization methods.
Journal of Computational Science. 18, 85–94.
mla: Gajda-Zagorska, Ewa P., et al. “A Multi Objective Memetic Inverse Solver Reinforced
by Local Optimization Methods.” Journal of Computational Science, vol.
18, Elsevier, 2017, pp. 85–94, doi:10.1016/j.jocs.2016.06.007.
short: E.P. Gajda-Zagorska, R. Schaefer, M. Smołka, D. Pardo, J. Alvarez Aramberri,
Journal of Computational Science 18 (2017) 85–94.
date_created: 2018-12-11T11:50:26Z
date_published: 2017-01-01T00:00:00Z
date_updated: 2023-09-20T11:29:44Z
day: '01'
ddc:
- '000'
department:
- _id: ChWo
doi: 10.1016/j.jocs.2016.06.007
external_id:
isi:
- '000393528700009'
file:
- access_level: open_access
content_type: application/pdf
creator: dernst
date_created: 2019-01-18T08:43:16Z
date_updated: 2019-01-18T08:43:16Z
file_id: '5842'
file_name: 2016_jocs_ewa.pdf
file_size: 1083911
relation: main_file
success: 1
file_date_updated: 2019-01-18T08:43:16Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
language:
- iso: eng
month: '01'
oa: 1
oa_version: Submitted Version
page: 85 - 94
publication: Journal of Computational Science
publication_identifier:
issn:
- '18777503'
publication_status: published
publisher: Elsevier
publist_id: '6206'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A multi objective memetic inverse solver reinforced by local optimization methods
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 18
year: '2017'
...
---
_id: '998'
abstract:
- lang: eng
text: 'A major open problem on the road to artificial intelligence is the development
of incrementally learning systems that learn about more and more concepts over
time from a stream of data. In this work, we introduce a new training strategy,
iCaRL, that allows learning in such a class-incremental way: only the training
data for a small number of classes has to be present at the same time and new
classes can be added progressively. iCaRL learns strong classifiers and a data
representation simultaneously. This distinguishes it from earlier works that were
fundamentally limited to fixed data representations and therefore incompatible
with deep learning architectures. We show by experiments on CIFAR-100 and ImageNet
ILSVRC 2012 data that iCaRL can learn many classes incrementally over a long period
of time where other strategies quickly fail. '
article_processing_charge: No
author:
- first_name: Sylvestre Alvise
full_name: Rebuffi, Sylvestre Alvise
last_name: Rebuffi
- first_name: Alexander
full_name: Kolesnikov, Alexander
id: 2D157DB6-F248-11E8-B48F-1D18A9856A87
last_name: Kolesnikov
- first_name: Georg
full_name: Sperl, Georg
id: 4DD40360-F248-11E8-B48F-1D18A9856A87
last_name: Sperl
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier
and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587'
apa: 'Rebuffi, S. A., Kolesnikov, A., Sperl, G., & Lampert, C. (2017). iCaRL:
Incremental classifier and representation learning (Vol. 2017, pp. 5533–5542).
Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA,
United States: IEEE. https://doi.org/10.1109/CVPR.2017.587'
chicago: 'Rebuffi, Sylvestre Alvise, Alexander Kolesnikov, Georg Sperl, and Christoph
Lampert. “ICaRL: Incremental Classifier and Representation Learning,” 2017:5533–42.
IEEE, 2017. https://doi.org/10.1109/CVPR.2017.587.'
ieee: 'S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental
classifier and representation learning,” presented at the CVPR: Computer Vision
and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.'
ista: 'Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. 2017. iCaRL: Incremental classifier
and representation learning. CVPR: Computer Vision and Pattern Recognition vol.
2017, 5533–5542.'
mla: 'Rebuffi, Sylvestre Alvise, et al. ICaRL: Incremental Classifier and Representation
Learning. Vol. 2017, IEEE, 2017, pp. 5533–42, doi:10.1109/CVPR.2017.587.'
short: S.A. Rebuffi, A. Kolesnikov, G. Sperl, C. Lampert, in:, IEEE, 2017, pp. 5533–5542.
conference:
end_date: 2017-07-26
location: Honolulu, HA, United States
name: 'CVPR: Computer Vision and Pattern Recognition'
start_date: 2017-07-21
date_created: 2018-12-11T11:49:37Z
date_published: 2017-04-14T00:00:00Z
date_updated: 2023-09-22T09:51:58Z
day: '14'
department:
- _id: ChLa
- _id: ChWo
doi: 10.1109/CVPR.2017.587
ec_funded: 1
external_id:
isi:
- '000418371405066'
intvolume: ' 2017'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1611.07725
month: '04'
oa: 1
oa_version: Submitted Version
page: 5533 - 5542
project:
- _id: 2532554C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '308036'
name: Lifelong Learning of Visual Scene Understanding
publication_identifier:
isbn:
- 978-153860457-1
publication_status: published
publisher: IEEE
publist_id: '6400'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'iCaRL: Incremental classifier and representation learning'
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2017
year: '2017'
...
---
_id: '839'
abstract:
- lang: eng
text: 'This thesis describes a brittle fracture simulation method for visual effects
applications. Building upon a symmetric Galerkin boundary element method, we first
compute stress intensity factors following the theory of linear elastic fracture
mechanics. We then use these stress intensities to simulate the motion of a propagating
crack front at a significantly higher resolution than the overall deformation
of the breaking object. Allowing for spatial variations of the material''s toughness
during crack propagation produces visually realistic, highly-detailed fracture
surfaces. Furthermore, we introduce approximations for stress intensities and
crack opening displacements, resulting in both practical speed-up and theoretically
superior runtime complexity compared to previous methods. While we choose a quasi-static
approach to fracture mechanics, ignoring dynamic deformations, we also couple
our fracture simulation framework to a standard rigid-body dynamics solver, enabling
visual effects artists to simulate both large scale motion, as well as fracturing
due to collision forces in a combined system. As fractures inside of an object
grow, their geometry must be represented both in the coarse boundary element mesh,
as well as at the desired fine output resolution. Using a boundary element method,
we avoid complicated volumetric meshing operations. Instead we describe a simple
set of surface meshing operations that allow us to progressively add cracks to
the mesh of an object and still re-use all previously computed entries of the
linear boundary element system matrix. On the high resolution level, we opt for
an implicit surface representation. We then describe how to capture fracture surfaces
during crack propagation, as well as separate the individual fragments resulting
from the fracture process, based on this implicit representation. We show results
obtained with our method, either solving the full boundary element system in every
time step, or alternatively using our fast approximations. These results demonstrate
that both of these methods perform well in basic test cases and produce realistic
fracture surfaces. Furthermore we show that our fast approximations substantially
out-perform the standard approach in more demanding scenarios. Finally, these
two methods naturally combine, using the full solution while the problem size
is manageably small and switching to the fast approximations later on. The resulting
hybrid method gives the user a direct way to choose between speed and accuracy
of the simulation. '
acknowledgement: "ERC H2020 programme (grant agreement no. 638176)\r\nFirst of all,
let me thank my committee members, especially my supervisor, Chris\r\nWojtan, for
supporting me throughout my PhD. Obviously, none of this work would\r\nhave been
possible without you.\r\nFurthermore, Thank You to all the people who have contributed
to this work in various\r\nways, in particular Martin Schanz and his group for providing
and supporting the\r\nHyENA boundary element library, as well as Eder Miguel and
Morten Bojsen-Hansen\r\nfor (repeatedly) proof reading and providing valuable suggestions
during the writing\r\nof this thesis.\r\nI would also like to thank Bernd Bickel,
and all the members – past and present – of his\r\nand Chris’ research groups at
IST Austria for always providing honest and insightful\r\nfeedback throughout many
joint group meetings, as well as Christopher Batty, Eitan\r\nGrinspun, and Fang
Da for many insights into boundary element methods during our\r\ncollaboration.\r\nAs
only virtual objects have been harmed in the process of creating this work, I would\r\nlike
to acknowledge the Stanford scanning repository for providing the “Bunny” and\r\n“Armadillo”
models, the AIM@SHAPE repository for “Pierre’s hand, watertight”, and\r\nS. Gainsbourg
for the “Column” via Archive3D.net. Sorry for breaking these models\r\nin many different
ways.\r\n"
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: David
full_name: Hahn, David
id: 357A6A66-F248-11E8-B48F-1D18A9856A87
last_name: Hahn
citation:
ama: Hahn D. Brittle fracture simulation with boundary elements for computer graphics.
2017. doi:10.15479/AT:ISTA:th_855
apa: Hahn, D. (2017). Brittle fracture simulation with boundary elements for
computer graphics. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_855
chicago: Hahn, David. “Brittle Fracture Simulation with Boundary Elements for Computer
Graphics.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_855.
ieee: D. Hahn, “Brittle fracture simulation with boundary elements for computer
graphics,” Institute of Science and Technology Austria, 2017.
ista: Hahn D. 2017. Brittle fracture simulation with boundary elements for computer
graphics. Institute of Science and Technology Austria.
mla: Hahn, David. Brittle Fracture Simulation with Boundary Elements for Computer
Graphics. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_855.
short: D. Hahn, Brittle Fracture Simulation with Boundary Elements for Computer
Graphics, Institute of Science and Technology Austria, 2017.
date_created: 2018-12-11T11:48:47Z
date_published: 2017-08-14T00:00:00Z
date_updated: 2024-02-21T13:48:02Z
day: '14'
ddc:
- '004'
- '005'
- '006'
- '531'
- '621'
degree_awarded: PhD
department:
- _id: ChWo
doi: 10.15479/AT:ISTA:th_855
ec_funded: 1
file:
- access_level: open_access
checksum: 6c1ae8c90bfaba5e089417fefbc4a272
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:46Z
date_updated: 2020-07-14T12:48:13Z
file_id: '5100'
file_name: IST-2017-855-v1+1_thesis_online_pdfA.pdf
file_size: 14596191
relation: main_file
- access_level: closed
checksum: 421672f68d563b029869c5cf1713f919
content_type: application/zip
creator: dernst
date_created: 2019-04-05T08:40:30Z
date_updated: 2020-07-14T12:48:13Z
file_id: '6207'
file_name: 2017_thesis_Hahn_source.zip
file_size: 15060566
relation: source_file
file_date_updated: 2020-07-14T12:48:13Z
has_accepted_license: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-sa/4.0/
month: '08'
oa: 1
oa_version: Published Version
page: '124'
project:
- _id: 2533E772-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '638176'
name: Efficient Simulation of Natural Phenomena at Extremely Large Scales
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
publist_id: '6809'
pubrep_id: '855'
related_material:
record:
- id: '1362'
relation: part_of_dissertation
status: public
- id: '1633'
relation: part_of_dissertation
status: public
- id: '5568'
relation: popular_science
status: public
status: public
supervisor:
- first_name: Christopher J
full_name: Wojtan, Christopher J
id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87
last_name: Wojtan
orcid: 0000-0001-6646-5546
title: Brittle fracture simulation with boundary elements for computer graphics
tmp:
image: /images/cc_by_sa.png
legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode
name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC
BY-SA 4.0)
short: CC BY-SA (4.0)
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2017'
...