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

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

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

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.

Original languageEnglish (US)
Title of host publication16th International Symposium on Medical Information Processing and Analysis
EditorsEduardo Romero, Natasha Lepore, Jorge Brieva, Marius Linguraru
PublisherSPIE
ISBN (Electronic)9781510639911
DOIs
StatePublished - Nov 3 2020
Event16th International Symposium on Medical Information Processing and Analysis 2020 - Lima, Virtual, Peru
Duration: Oct 3 2020Oct 4 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11583
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference16th International Symposium on Medical Information Processing and Analysis 2020
Country/TerritoryPeru
CityLima, Virtual
Period10/3/2010/4/20

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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