Human Pose Tracking from RGB Inputs | IEEE Conference Publication | IEEE Xplore

Human Pose Tracking from RGB Inputs


Abstract:

In the context of Virtual and Augmented Reality, in order to allow systems to provide natural interaction through gestures and general understanding of user body behavior...Show More

Abstract:

In the context of Virtual and Augmented Reality, in order to allow systems to provide natural interaction through gestures and general understanding of user body behavior it is fundamental to obtain the configuration of human poses. Once achieved, the goal of obtaining such poses from RGB images through cameras brings the possibility of a wide range of applications in the areas of security (i.e.: local activity monitoring), healthcare (i.e.: postural analysis) and entertainment (i.e.: games and animations motion capture). However, the acquisition of human poses solely through RGB images is still considered a challenge, once that pure visual data doesnt explicitly give us information about the human body joints (keypoints in pixels) localization in the image. In this work we propose the a machine learning method, more specifically deep learning based on convolutional neural networks, capable of tackling this problem.
Date of Conference: 28-30 October 2018
Date Added to IEEE Xplore: 19 August 2019
ISBN Information:
Conference Location: Foz do Iguacu, Brazil

Contact IEEE to Subscribe

References

References is not available for this document.