MonoEye: A human motion capture system using a single wearable camera


Date:
October 21, 2020
Source:
Tokyo Institute of Technology
Summary:
Researchers have developed a new human motion capture system that
consists of a single ultra-wide fisheye camera mounted on the user's
chest. The simplicity of their system could be conducive to a wide
range of applications in the sports, medical and entertainment
fields.



FULL STORY ========================================================================== Researchers at Tokyo Institute of Technology (Tokyo Tech) and Carnegie
Mellon University have together developed a new human motion capture
system that consists of a single ultra-wide fisheye camera mounted on the user's chest. The simplicity of their system could be conducive to a wide
range of applications in the sports, medical and entertainment fields.


========================================================================== Computer vision-based technologies are advancing rapidly owing to recent developments in integrating deep learning. In particular, human motion
capture is a highly active research area driving advances for example
in robotics, computer generated animation and sports science.

Conventional motion capture systems in specially equipped studios
typically rely on having several synchronized cameras attached to the
ceiling and walls that capture movements by a person wearing a body suit
fitted with numerous sensors. Such systems are often very expensive
and limited in terms of the space and environment in which the wearer
can move.

Now, a team of researchers led by Hideki Koike at Tokyo Tech present a
new motion capture system that consists of a single ultra-wide fisheye
camera mounted on the user's chest. Their design not only overcomes the
space constraints of existing systems but is also cost-effective.

Named MonoEye, the system can capture the user's body motion as well as
the user's perspective, or 'viewport'. "Our ultra-wide fisheye lens has
a 280- degree field-of-view and it can capture the user's limbs, face,
and the surrounding environment," the researchers say.

To achieve robust multimodal motion capture, the system has been designed
with three deep neural networks capable of estimating 3D body pose,
head pose and camera pose in real-time.

Already, the researchers have trained these neural networks with an
extensive synthetic dataset consisting of 680,000 renderings of people
with a range of body shapes, clothing, actions, background and lighting conditions, as well as 16,000 frames of photo-realistic images.

Some challenges remain, however, due to the inevitable domain gap between synthetic and real-world datasets. The researchers plan to keep expanding
their dataset with more photo-realistic images to help minimize this
gap and improve accuracy.

The researchers envision that the chest-mounted camera could go on to
be transformed into an everyday accessory such as a tie clip, brooch or
sports gear in future.

The team's work will be presented at the 33rd ACM Symposium on User
Interface Software and Technology (UIST), a leading forum for innovations
in human- computer interfaces, to be held virtually on 20-23 October 2020.


========================================================================== Story Source: Materials provided by Tokyo_Institute_of_Technology. Note: Content may be edited for style and length.


==========================================================================


Link to news story: https://www.sciencedaily.com/releases/2020/10/201021112416.htm

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