3D Motion Capture Market and its key opportunities and challenges

The 3D Motion Capture Market was valued at USD 111.6 Million in 2016 and is expected to reach USD 204.0 Million by 2022, at a CAGR of 10.28% during the forecast period, as per a report by MarketsandMarkets.

The 3D Motion Capture Market was valued at USD 111.6 Million in 2016 and is expected to reach USD 204.0 Million by 2022, at a CAGR of 10.28% during the forecast period, as per a report by MarketsandMarkets. 

How growing adoption for biomechanics research in medical and industrial application areas offer multiple opportunities?

The 3D motion capture systems have been gaining popularity and are expected to find wide application areas such as gait analysis, clinical motion analysis, biomechanics research, and sports science. For instance, Rokoko Electronics, Inc. (U.S.) developed a low cost motion capture software suit named Salto, which has applications for medical and biophysics. The company is working with the University of Southern Denmark on Psychiatric Live Animation Intervention (PLAI) that aims to create a software tool along with the Salto to treat children on the autism spectrum, which is a type of mental disorder of a person. Moreover, the company developed the Smartsuit Pro, which is a wireless body suit with embedded sensors that enables the user to achieve a natural physical presence in the virtual world.

In industrial applications, 3D motion capture is used for automation of machines, designing, and measurement of machine movements. Moreover, the motion capture systems can be used for OEM applications. For instance, in a container crane anti-sway application, the motion data from a single camera can be used in a crane head position to analyze the positional information from the camera system.

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Why need of high-end processors poses a challenge?

The motion capture systems utilize cameras to capture the movement and then process these collated images to generate the desired result. The processing is carried out by using a computer system, which is capable of handling the bulk amount of data. The existing CPU and GPU technology platforms are not up to the mark as desired by the motion capture system. This is because the data generated is enormous from the cameras and consumes time to process the collated data. For instance, during a baseball game motion capture is done to determine various parameters for the games such as baseball pitches. The systems capture data at 300 frames per second using multiple image capture platforms. These images are then processed using biomechanics measurements to report angles, distance, and velocities to determine hand or wrist has traveled X number of feet in distance and velocity of travel. This is done using multiple GPUs capable of processing data rapidly at a high-level of accuracy and in real time. Despite the usage of such high-end processing systems, the data processing consumes a significant amount of time due to which high-end powered processors are required.

Real-time data with exceptional spatial and temporal accuracy

The 3D motion capture systems have evolved with time and are capable of providing highly accurate data, which can be used for a wide range of applications as well as research projects. These systems provide real-time data, which can be mapped to create animations of desired quality and accuracy, thereby making these systems ideal for virtual reality as well as other feedback applications. These systems are also capable of removing any false signals that are created due to reflections. Various companies are developing 3D motion capture systems with exceptional accuracy to collect precise data from the motion of objects or a person for high-level animated content, which can then be cleaned-up, retargeted, and reformed using a software such as MotionBuilder. For instance, Northern Digital, Inc. (Canada) has developed the 3D Investigator, which is an advanced motion capture technology delivering research-grade data at maximum quality. The device offers highly accurate data, which is free of any falsifications occurring due to reflections along with the absence of data sorting during the collation phase. The device is ideal for applications such as posture and balance, hand and foot biomechanics, infant studies, neurology, spine research, sports biomechanics, motor control, and gait analysis.

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