The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis

Chromý, Adam; Žalud, Luděk

doi:10.3390/s20226656

Cited by 2 publications

(1 citation statement)

References 49 publications

(78 reference statements)

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“…With human pose estimation, tracking a person or multiple people in real space can be done at an incredibly granular level. This powerful capability unlocks a wide range of industrial applications [1][2][3][4][5][6][7][8], including gaming, animation, motion transfer, augmented reality, human-robot cooperation and training, biomechanical analysis for medical/healthcare, sports fields, gesture control, autonomous driving, human fall detection, action prediction, security and surveillance, etc.…”

Section: Introductionmentioning

confidence: 99%

Top-Down System for Multi-Person 3D Absolute Pose Estimation from Monocular Videos

Kaid

Brazey²,

Barra

et al. 2022

Sensors

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Two-dimensional (2D) multi-person pose estimation and three-dimensional (3D) root-relative pose estimation from a monocular RGB camera have made significant progress recently. Yet, real-world applications require depth estimations and the ability to determine the distances between people in a scene. Therefore, it is necessary to recover the 3D absolute poses of several people. However, this is still a challenge when using cameras from single points of view. Furthermore, the previously proposed systems typically required a significant amount of resources and memory. To overcome these restrictions, we herein propose a real-time framework for multi-person 3D absolute pose estimation from a monocular camera, which integrates a human detector, a 2D pose estimator, a 3D root-relative pose reconstructor, and a root depth estimator in a top-down manner. The proposed system, called Root-GAST-Net, is based on modified versions of GAST-Net and RootNet networks. The efficiency of the proposed Root-GAST-Net system is demonstrated through quantitative and qualitative evaluations on two benchmark datasets, Human3.6M and MuPoTS-3D. On all evaluated metrics, our experimental results on the MuPoTS-3D dataset outperform the current state-of-the-art by a significant margin, and can run in real-time at 15 fps on the Nvidia GeForce GTX 1080.

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Section: Introductionmentioning

confidence: 99%

Top-Down System for Multi-Person 3D Absolute Pose Estimation from Monocular Videos

Kaid

Brazey²,

Barra

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

Tomographic reconstruction from planar thermal imaging using convolutional neural network

Ledwoń

Sage

Juszczyk

et al. 2022

Sci Rep

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In this study, we investigate perspectives for thermal tomography based on planar infrared thermal images. Volumetric reconstruction of temperature distribution inside an object is hardly applicable in a way similar to ionizing-radiation-based modalities due to its non-penetrating character. Here, we aim at employing the autoencoder deep neural network to collect knowledge on the single-source heat transfer model. For that purpose, we prepare a series of synthetic 3D models of a cylindrical phantom with assumed thermal properties with various heat source locations, captured at different times. A set of planar thermal images taken around the model is subjected to initial backprojection reconstruction, then passed to the deep model. This paper reports the training and testing results in terms of five metrics assessing spatial similarity between volumetric models, signal-to-noise ratio, or heat source location accuracy. We also evaluate the assumptions of the synthetic model with an experiment involving thermal imaging of a real object (pork) and a single heat source. For validation, we investigate objects with multiple heat sources of a random location and temperature. Our results show the capability of a deep model to reconstruct the temperature distribution inside the object.

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The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis

Cited by 2 publications

References 49 publications

Top-Down System for Multi-Person 3D Absolute Pose Estimation from Monocular Videos

Top-Down System for Multi-Person 3D Absolute Pose Estimation from Monocular Videos

Tomographic reconstruction from planar thermal imaging using convolutional neural network

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