Automatic estimation of pose and falls in videos using computer vision model

Daniela A. Calvache, Hernán A. Bernal, Juan F. Guarín, Karen Aguía, Alvaro D. Orjuela-Cañón, Oscar J. Perdomo

Resultado de la investigación: Capítulo en Libro/Reporte/ConferenciaCapítulo (revisado por pares)revisión exhaustiva

Resumen

Human pose estimation is defined as the process of locating joints of a person or a crowd given an image or video. Currently, this estimation is widely used for the evaluation of athletes, workers, and the monitoring of patients in clinical settings. However, human pose estimation is not an easy task as it requires experts to manually assess the person’s position by using specialized equipment such as e-health devices (watches, bands, handles), markers, and high-cost cameras to monitor a limited scenario. The main goal of this article is to evaluate a marker-less low-cost computer vision system to get the automatic estimation of poses and fall detection on video by calculating the person’s joint angle with a high level of adaptability to any space. The proposed model is the first step in the construction of a tool that allows monitoring and generating alerts to prevent falls at home and clinical settings.

Idioma originalInglés estadounidense
Título de la publicación alojada16th International Symposium on Medical Information Processing and Analysis
EditoresEduardo Romero, Natasha Lepore, Jorge Brieva, Marius Linguraru
EditorialSPIE
ISBN (versión digital)9781510639911
DOI
EstadoPublicada - nov 3 2020
Evento16th International Symposium on Medical Information Processing and Analysis 2020 - Lima, Virtual, Perú
Duración: oct 3 2020oct 4 2020

Serie de la publicación

NombreProceedings of SPIE - The International Society for Optical Engineering
Volumen11583
ISSN (versión impresa)0277-786X
ISSN (versión digital)1996-756X

Conferencia

Conferencia16th International Symposium on Medical Information Processing and Analysis 2020
País/TerritorioPerú
CiudadLima, Virtual
Período10/3/2010/4/20

All Science Journal Classification (ASJC) codes

  • Materiales electrónicos, ópticos y magnéticos
  • Física de la materia condensada
  • Informática aplicada
  • Matemáticas aplicadas
  • Ingeniería eléctrica y electrónica

Huella

Profundice en los temas de investigación de 'Automatic estimation of pose and falls in videos using computer vision model'. En conjunto forman una huella única.

Citar esto