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Quantify human motion.

Digitize humans and receive real-time measurements. Data you can count on.

knee

Analyze

Gather important angles of the human motion and define good or bad thresholds.

tacho meter

Measure

Measure the velocity of specific human body parts to analyze movements.

human body

Compare

Evaluate poses and movements and compare them to a target goal.

We have opened the doors.

It is was too complex to implement and utilize human pose estimation in applications.

Use case:
Sports

The VAY Fitness Coach is a fully virtual personal coach for the smartphone. Users get real-time feedback on their pose and automatic progress tracking during their workout sessions.

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real time

Real-Time

Analyze human poses and create real-time response systems.

sensor

Markerless

Humans move the freest without any markers or sensors attached.

camera

Monocular

A single camera suffices to estimate human poses with us.

Unlimited possibilities

Turn the human body into a game controller. Build a virtual physio trainer or teach your employees to move ergonomically. You choose.

Workplace Safety

Ensure workplace wellness with our solution.

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Sports

Create real-time feedback systems to guide your users.

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Interactive Entertainment

Remove markers and let your users interact with your AR applications.

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Health

Teach your users to do physical exercises the right way.

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A plug-and-play solution.

Get started real quick with a few copy and pastes.

from vayai.vup.client import Client, IdTypes
client = Client('ssl://api.vay.ai:110').connect()
# Configure your session
client.send_metadata(uid='your-user-name', # Your user name goes here.
               task_type=IdTypes.Movement, # The desired type of analysis to perform.
               id=12345)                   # Specify the id of your analysis task.
sessionId = client.read_message().sessionId
# Now you are good to go, send your images...
client.send_image(image)
# and receive the results!
response = client.read_message()
# We offer the raw key points...
points = response.points
print(f'Nose: x={points.nose.x}, y={points.nose.y}, z={points.nose.z}')
# ... as well as detailed feedback.
feedback = response.feedback