Vaš brskalnik ne omogoča JavaScript!
JavaScript je nujen za pravilno delovanje teh spletnih strani. Omogočite JavaScript ali pa uporabite sodobnejši brskalnik.
Nacionalni portal odprte znanosti
Odprta znanost
DiKUL
slv
|
eng
Iskanje
Brskanje
Novo v RUL
Kaj je RUL
V številkah
Pomoč
Prijava
Reflection probe interpolation for fast and accurate rendering of reflective materials
ID
Gojković, Katarina
(
Avtor
),
ID
Lesar, Žiga
(
Avtor
),
ID
Marolt, Matija
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(6,76 MB)
MD5: 15C1BE35EC9AF4E43129C67FBB777F17
Galerija slik
Izvleček
In this paper, we aim to improve rendering reflections using environment maps on moving reflective objects. Such scenarios require multiple reflection probes to be positioned at various locations in a scene. During rendering, the closest reflection probe is typically chosen as the environment map of a specific object, resulting in sharp transitions between the rendered reflections when the object moves around the scene. To solve this problem, we developed two convolutional neural networks that dynamically synthesize the best possible environment map at a given point in the scene. The first network generates an environment map from the coordinates of a given point through a decoder architecture. In the second approach, we triangulated the scene and captured environment maps at the triangle vertices – these represent reflection probes. The second network receives at the input three environment maps captured at the vertices of the triangle containing the query point, along with the distances between the query point and the vertices. Through an encoder-decoder architecture, the second network performs smart interpolation of the three environment maps. Both approaches are based on the phenomenon of overfitting, which made it necessary to train each network individually for specific scenes. Both networks are successful at predicting environment maps at arbitrary locations in the scene, even if these locations were not part of the training set. The accuracy of the predictions strongly depends on the complexity of the scene itself.
Jezik:
Angleški jezik
Ključne besede:
refection probes
,
interpolation
,
convolutional neural network
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FRI - Fakulteta za računalništvo in informatiko
Leto izida:
2024
Št. strani:
Str. 61-70
Številčenje:
Vol. 32, no. 1/2
PID:
20.500.12556/RUL-160035
UDK:
004
ISSN pri članku:
1213-6964
DOI:
10.24132/JWSCG.2024.7
COBISS.SI-ID:
202681603
Datum objave v RUL:
09.08.2024
Število ogledov:
294
Število prenosov:
42
Metapodatki:
Citiraj gradivo
Navadno besedilo
BibTeX
EndNote XML
EndNote/Refer
RIS
ABNT
ACM Ref
AMA
APA
Chicago 17th Author-Date
Harvard
IEEE
ISO 690
MLA
Vancouver
:
Kopiraj citat
Objavi na:
Gradivo je del revije
Naslov:
Journal of WSCG
Skrajšan naslov:
J. WSCG
Založnik:
Václav Skala-Union Agency
ISSN:
1213-6964
COBISS.SI-ID:
159710211
Licence
Licenca:
CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
Opis:
Najbolj omejujoča licenca Creative Commons. Uporabniki lahko prenesejo in delijo delo v nekomercialne namene in ga ne smejo uporabiti za nobene druge namene.
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
odsevne sonde
,
interpolacija
,
konvolucijska nevronska mreža
Podobna dela
Podobna dela v RUL:
Podobna dela v drugih slovenskih zbirkah:
Nazaj