An RGB/Infra-Red camera fusion approach for Multi-Person Pose Estimation in low light environments

Crescitelli, Viviana; Kosuge, Atsutake; Oshima, Takashi

doi:10.1109/sas48726.2020.9220059

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…The application of artificial intelligence allows the prediction of human posture, but it is a topic that is still expanding. There are applications such as OpenPose that evidence its versatility to work in collaboration with cameras, sensors, and other pose estimation libraries [25]. Such is so, [13] stated that to counteract the adverse effects of occlusion, there is a tendency to delimit the body joints from 3D human skeleton data acquired from a library of stored postures, thus achieving better performance in all measurements.…”

Section: Discussionmentioning

confidence: 99%

Ergonomic Improvement to Reduce the Risk of Musculoskeletal Disorders (MSDS) in a Furniture Production Workshop

Cama Machado,

Casas Rodrigo,

Taquía Gutierrez

2023

Advances in Transdisciplinary Engineering

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The present research work has the purpose of simulating an ergonomic improvement in the furniture production workshop for the areas that show a higher risk of musculoskeletal disorders. In this sense, ergonomics methods and instruments such as the Nordic questionnaire were used to measure the body areas, due to the increase in cases of MSDs related to physical work in the upholstery sector. These disorders develop due to the lack of an adequate ergonomic design and the lack of early identification that prioritizes the well-being of workers. Thus, NIOSH, RULA and OWAS methodologies were applied to evaluate the level of risk and lifting index before and after. These values were contrasted with Ergosoft Pro and 3DSSPP software to validate the design proposal. Thus, the risk level was reduced from a value of 4 to 1 and the uplift index from 3.8 to 0.99. In addition, artificial intelligence was employed through the application of Open Pose to achieve the estimation of the arm angles in real time.

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Section: Discussionmentioning

confidence: 99%