Authors :
Rutuja Gajbhiye; Snehal Jarag; Pooja Gaikwad; Shweta Koparde
Volume/Issue :
Volume 7 - 2022, Issue 5 - May
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3aA9joA
DOI :
https://doi.org/10.5281/zenodo.6824903
Abstract :
The most important of yoga poses is known
around the world and proves the health benefits preached
by ancient sages. As yoga becomes more important, yoga
faces the following important challenges: Computer
vision technology provides a promising solution for
assessing human posture. However, these techniques are
rarely used in the areas of health and exercise, and there
are no specific references or projects. Named after yoga.
This white paper describes the different technologies that
can be used for pose estimation and summarize the best
ways to use them based on the ease of use of your Android
app application. The following describes the methodology
used to provide yoga pose estimation in Android
applications, how the app is modelled, and how each
component works. Pose estimation is a branch of
computer vision that deals with the recognition of the
individual parts that make up the body (usually the
human body). There are several ways to achieve this, The
approach I use starts with passing the incoming image
through a CNN classifier trained to look for people. When
the human body poses are recognized, the pose estimation
network searches for trained joints and limbs. The
computer can then display the image to the user using
markers that identify parts of the body.
Keywords :
Deep Learning, Machine Learning, Pose Estimation, OpenPose, PostNet, YogaPoses, CNN.
The most important of yoga poses is known
around the world and proves the health benefits preached
by ancient sages. As yoga becomes more important, yoga
faces the following important challenges: Computer
vision technology provides a promising solution for
assessing human posture. However, these techniques are
rarely used in the areas of health and exercise, and there
are no specific references or projects. Named after yoga.
This white paper describes the different technologies that
can be used for pose estimation and summarize the best
ways to use them based on the ease of use of your Android
app application. The following describes the methodology
used to provide yoga pose estimation in Android
applications, how the app is modelled, and how each
component works. Pose estimation is a branch of
computer vision that deals with the recognition of the
individual parts that make up the body (usually the
human body). There are several ways to achieve this, The
approach I use starts with passing the incoming image
through a CNN classifier trained to look for people. When
the human body poses are recognized, the pose estimation
network searches for trained joints and limbs. The
computer can then display the image to the user using
markers that identify parts of the body.
Keywords :
Deep Learning, Machine Learning, Pose Estimation, OpenPose, PostNet, YogaPoses, CNN.
