3-D Human Body Posture Reconstruction by Computer Vision

Jacobo E. Cruz-Silva, Jesús Y. Montiel-Pérez, Humberto Sossa-Azuela

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Human limb movement sensing is crucial in different areas of science. In this paper, a method for sensing human limb movement and the subsequent reconstruction in a 3-D plane is described. The sensors used in this task are four Microsoft Kinect, which has depth and RGB cameras. Depth images are processed by artificial vision algorithms to delimit an area where the movements will be performed. In the other hand, RGB images are processed by a Convolutional Neural Network to acquire a series of specific points which correspond to the human body’s joints. A comparison of the proposed algorithm performance is also described. The equations that relate the information in two dimensions are obtained by processing the four sensors are used to generate a skeleton in 3-D.

Idioma originalInglés
Título de la publicación alojadaAdvances in Soft Computing - 18th Mexican International Conference on Artificial Intelligence, MICAI 2019, Proceedings
EditoresLourdes Martínez-Villaseñor, Ildar Batyrshin, Antonio Marín-Hernández
EditorialSpringer
Páginas579-588
Número de páginas10
ISBN (versión impresa)9783030337483
DOI
EstadoPublicada - 2019
Evento18th Mexican International Conference on Artificial Intelligence, MICAI 2019 - Xalapa, México
Duración: 27 oct. 20192 nov. 2019

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen11835 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia18th Mexican International Conference on Artificial Intelligence, MICAI 2019
País/TerritorioMéxico
CiudadXalapa
Período27/10/192/11/19

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