Evidence map›Paper›PMID 36236323›Full record

ArticleSensors (Basel, Switzerland)2022

Physics-Based Simulation of Soft-Body Deformation Using RGB-D Data.

Daeun Kang, Jaeseok Moon, Saeyoung Yang, Taesoo Kwon, Yejin Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Daeun KangDepartment of Computer Science, Hanyang University, Seoul 04763, Korea.ORCID 0000-0003-2362-7669
Jaeseok MoonDepartment of Computer Science, Hanyang University, Seoul 04763, Korea.
Saeyoung YangDepartment of Computer Science, Hanyang University, Seoul 04763, Korea.
Taesoo KwonDepartment of Computer Science, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-9253-2156
Yejin KimSchool of Games, Hongik University, Sejong 30016, Korea.ORCID 0000-0002-4209-4266

Funding

Institute for Information and Communications Technology Promotion 2017-0-01849Institute for Information and Communications Technology Promotion 2021-0-00320National Research Foundation of Korea 2021R1F1A1046513
6 · The paper itself

Abstract

Providing real-time interaction in an immersive environment has drawn considerable attention in the virtual training fields. Physics-based simulations are suitable for such environments; however, they require the definition and adjustment of coefficients that determine material properties, making the methods more complex and time-consuming. In this paper, we introduce a novel approach to simulating the soft-body deformation of an observed object. Using an off-the-shelf RGB-D sensor, the proposed approach tracks an object's movement and simulates its deformation in an iterative manner. Polygonal models with different resolutions are used to improve the simulation speed and visual quality. During the simulation process, a low-resolution model is used for surface deformation using neighboring feature points detected from the sensor, and a volumetric model is added for internal force estimation. To visualize the observed model in detail, the deformed and low-resolution model is mapped to a high-resolution model using mean value coordinate interpolation. To handle topological deformations, such as cutting or tearing, a part intersected by a cutting tool is recognized by the sensor and responds to external forces. As shown in the experimental results, our approach generates convincing deformations of observed objects in real time.

Indexed as

PhysicsComputer Simulationobject trackingphysics-based simulationRGB-D datasoft-body deformationtopological editing

Identifiers

PMID36236323
PMCPMC9571817

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.