Detail publikace

ICTree: Automatic Perceptual Metrics for Tree Models

POLÁŠEK, T. HRŮŠA, D. BENEŠ, B. ČADÍK, M.

Originální název

ICTree: Automatic Perceptual Metrics for Tree Models

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Many algorithms for synthetic tree generation exist, but the visual quality of the generated models is unknown. This problem is usually solved by performing limited user studies or by side-by-side comparison. We introduce an automated system for quality assessment of the tree model based on their perception. We conducted a user study in which over one million pairs of images were compared to collect subjective perceptual scores of generated trees. The perceptual score was used to train two neural-network-based predictors. A view independent ICTreeF uses the tree models geometric features that are easy to extract from any model. The second is ICTreeI that estimates the perceived visual quality of a tree from its image. Moreover, to provide an insight into the problem, we deduce intrinsic attributes and evaluate which features make trees look like real trees. In particular, we show that branching angles, length of branches, and widths are critical for perceived realism.

Klíčová slova

Evaluation & Perception, Natural Phenomena, User Studies, Generative 3D Modeling, Perception

Autoři

POLÁŠEK, T.; HRŮŠA, D.; BENEŠ, B.; ČADÍK, M.

Vydáno

10. 12. 2021

ISSN

0730-0301

Periodikum

ACM TRANSACTIONS ON GRAPHICS

Ročník

40

Číslo

6

Stát

Spojené státy americké

Strany od

1

Strany do

15

Strany počet

15

URL

https://doi.org/10.1145/3478513.3480519

BibTex

@article{BUT168956,
  author="POLÁŠEK, T. and HRŮŠA, D. and BENEŠ, B. and ČADÍK, M.",
  title="ICTree: Automatic Perceptual Metrics for Tree Models",
  journal="ACM TRANSACTIONS ON GRAPHICS",
  year="2021",
  volume="40",
  number="6",
  pages="1--15",
  doi="10.1145/3478513.3480519",
  issn="0730-0301",
  url="https://doi.org/10.1145/3478513.3480519"
}