Potential Application of Deep learning to Boost 3D Motion Capture System Market

Motion Capture (mocap) enables for movement of people to be digitally recorded. 3D Motion Capture System provides its users with the ability to capture movements by using cameras and sensors. It then processes the images or videos captured by processing software. These systems are used in several industries ranging from healthcare, sports, media and entertainment, military and defense, and others.

Three-dimensional motion tracking enhances the interaction between a human and a computer by playing an essential role in the animation of a 3-D model. Real-time information and the amount of data produced by motion tracking are provided to the computer for such interaction.

Optical cameras are currently popularly used to track movement. However, on the downside, they struggle with accuracy and reliability. In case a small animal or a finger, or any kind of object obscures the view of the camera, it will not be able to detect the motion. Similarly, Magnetic Tracking Technology is also used for this purpose but encounters limitations like creating bias and magnetic sources having problem of dead angle or bulky markers.

Looking at these problems, a new sensing method has been developed to make tracking movement easier and efficient. This sensing method uses a deep learning structure-aware temporal bilateral filter to capture dexterous 3-D motion data from a magnetic flux sensor array. This technology can be used for various purposes like tracking hand motions to ensure the creation of smooth animation, recording detailed movements of small animals by biologists, tracking of the flow of fluid by scientists, finger movements, and objects being manipulated by users in virtual reality can be tracked by researchers.

The new sensing method also compensates the data in order to reconstruct smooth and accurate motion. Its markers do not require batteries, which lead to maximization of observation time. Hence, it can track multiple LC coils at 100Hz at millimeter level accuracy. Furthermore, tracking loss that occurs due to the dead angle can be reconstructed as the system has self-learning ability.

The Global 3D Motion Capture System Market is expected to have good growth due to the increase in applicability of these systems in several industries. Hence, its market is predicted to grow significantly in the next five years. These systems help in capturing the real-time motion of objects and humans for acquiring the appropriate level of animation. The development of new games and the decent growth in the gaming population are projected to significantly boost the adoption of these systems and increase market growth in the coming years. The development of VR games for gaming consoles and the booming adoption of these games will further bolster the market growth.