A framework to design 3D interaction assistance in constraints-based virtual environments

Essabbah, Mouna; Bouyer, Guillaume; Otmane, Samir; Mallem, Malik

doi:10.1007/s10055-014-0247-z

Cited by 6 publications

(2 citation statements)

References 32 publications

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“…For the case of a 60

m^{2}

real presentation area, the average MIPS caused by the ontology modeling method is 1,825 MIPS, which is 21.2% less than that of particle modeling method. The ontology modeling method contributes to clustering of the out‐of‐order objects into different groups, which further reduces voxel redundancy .…”

Section: Simulation and Analysismentioning

confidence: 99%

A low‐complexity virtual reality modeling method based on ontology grid sparsity

Wan

Deng

Yang

2017

Comp Applic In Engineering

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This paper focuses on an innovative low‐complexity modeling method for virtual reality. Voxels are the basic unit of pixels in 3D (three dimensions), and when stored and processed in a computer, they contain more data redundancy than the demand for actual human vision presentations. This excess is known as voxel redundancy. The reason for the redundancy is that infinite‐dimensional expansion and heterogeneous voxel features have merged in modeling methods. The major voxel compressions and human factors correlations are important to consider. Therefore, we propose a novel low‐complexity virtual reality based on ontology grid sparsity. The redundancy performance of the existing virtual reality modeling methods is first analyzed. The high‐dimension modeling method is designed to describe the base elements that are needed for humans to distinguish what is actually perceived. Based on the ontology theory, grid sparsity is exploited to construct the correlation model. We set up the relevant degree and sensitivity level calculations to classify the correlations between ontology features and other features. The features with weak sensitivity are ignored or merged, which successfully reduces the dimensions and redundancy that are needed to represent virtual items. Visual feature integration combines human factors into a voxel model. Finally, we build the virtual laboratory as a test case in the Unity 3D and 3DMax environment. The tests demonstrate that the new modeling method offers 21.2% and 34.7% of presentation delay and redundancy improvement, respectively.

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“…For the case of a 60

m^{2}

Section: Simulation and Analysismentioning

confidence: 99%

A low‐complexity virtual reality modeling method based on ontology grid sparsity

Wan

Deng

Yang

2017

Comp Applic In Engineering

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“…With the thriving developments of the applications in virtual reality such as 3D films, virtual Human-Machine Interaction (Essabbah et al 2014;Hernoux and Christmann 2015) and virtual agents (Chen et al 2016;Qu et al 2013), 3D human face analysis is considered to be one of the most important researches (Lee et al 2007) in this area. Compared to the analysis of 2D facial data, 3D facial analysis can achieve higher accuracy and efficiency than its equivalent 2D methods through the addition of another dimension.…”

Section: Introductionmentioning

confidence: 99%

Dense 3D facial reconstruction from a single depth image in unconstrained environment

Shu

Wang

et al. 2017

Virtual Reality

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With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step for those virtual reality tasks. Due to information provided by an additional dimension, 3D facial reconstruction enables aforementioned tasks to be achieved with higher accuracy than those based on 2D facial analysis. The denser the 3D facial model is, the more information it could provide. However, most existing dense 3D facial reconstruction methods require complicated processing and high system cost. To this end, this paper presents a novel method that simplifies the process of dense 3D facial reconstruction by employing only one frame of depth data obtained with an off-the-shelf RGB-D sensor. The experiments showed competitive results with real world data.

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A fuzzy interaction scheme of mid-air gesture elicitation

Feng

Cheng

2019

Journal of Visual Communication and Image Representation

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A framework to design 3D interaction assistance in constraints-based virtual environments

Cited by 6 publications

References 32 publications

A low‐complexity virtual reality modeling method based on ontology grid sparsity

A low‐complexity virtual reality modeling method based on ontology grid sparsity

Dense 3D facial reconstruction from a single depth image in unconstrained environment

A fuzzy interaction scheme of mid-air gesture elicitation

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