PTRM: Perceived Terrain Realism Metric

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU144298" target="_blank" >RIV/00216305:26230/22:PU144298 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21230/22:00358984

Result on the web

<a href="https://dl.acm.org/doi/10.1145/3514244" target="_blank" >https://dl.acm.org/doi/10.1145/3514244</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3514244" target="_blank" >10.1145/3514244</a>

Result language

angličtina

Original language name

PTRM: Perceived Terrain Realism Metric

Original language description

Terrains are visually prominent and commonly needed objects in many computer graphics applications. While there are many algorithms for synthetic terrain generation, it is rather difficult to assess the realism of a generated output. This paper presents a first step towards the direction of perceptual evaluation for terrain models. We gathered and categorized several classes of real terrains, and we generated synthetic terrain models using computer graphics methods. The terrain geometries were rendered by using the same texturing, lighting, and camera position. Two studies on these image sets were conducted, ranking the terrains perceptually, and showing that the synthetic terrains are perceived as lacking realism compared to the real ones. We provide insight into the features that affect the perceived realism by a quantitative evaluation based on localized geomorphology-based landform features (geomorphons) that categorize terrain structures such as valleys, ridges, hollows, etc. We show that the presence or absence of certain features has a significant perceptual effect. The importance and presence of the terrain features were confirmed by using a generative deep neural network that transferred the features between the geometric models of the real terrains and the synthetic ones. The feature transfer was followed by another perceptual experiment that further showed their importance and effect on perceived realism. We then introduce Perceived Terrain Realism Metrics (PTRM) that estimates human perceived realism of a terrain represented as a digital elevation map by relating distribution of terrain features with their perceived realism. This metric can be used on a synthetic terrain, and it will output an estimated level of perceived realism. We validated the proposed metrics on real and synthetic data and compared them to the perceptual studies.

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LTAIZ19004" target="_blank" >LTAIZ19004: Deep-Learning Approach to Topographical Image Analysis</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

ACM Transactions on Applied Perception

ISSN

1544-3558

e-ISSN

1544-3965

Volume of the periodical

19

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

22

Pages from-to

1-22

UT code for WoS article

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EID of the result in the Scopus database

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