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Optical Motion Capture System FAQ
An optical motion capture system is a high-precision solution where cameras with built-in dedicated processors interface seamlessly with analysis software in real time. The dedicated cameras track reflective markers attached to an object to generate 2D coordinate data. The software then integrates and analyzes this 2D data from multiple cameras through a process called calibration to construct complete 3D position data. Ultimately, this 3D data enables precise motion analysis for various subjects, including the human body and robotics.
To accurately capture the movement of a 3D object, both rotational and positional values are required. Conventional IMU (Inertial Measurement Unit) systems measure rotational values first and then estimate positional values through mathematical calculations. As a result, position errors tend to accumulate as movements become larger or travel distances increase. In contrast, position-based optical systems capture precise positional data right from the start, generating highly accurate data without accumulated errors even during vigorous movements, while rotational values can still be easily derived through calculations. Furthermore, while IMU systems are largely specialized for the human body, optical systems offer exceptional versatility; you can capture the motion of literally any object—whether it is a person, a robot, an animal, or an object—simply by attaching markers to it.
The core requirement of an optical motion capture system is that the infrared cameras must track the markers without interruption. Therefore, the cameras must be arranged around the perimeter to overlook the entire capture volume where the markers will move. To extract accurate 3D data, a single marker must be captured by at least two cameras simultaneously. This means you must carefully arrange the cameras across various angles and heights to ensure that markers remain within the field of view of at least two cameras at all times, preventing data loss caused by body occlusion or blind spots.
Camera resolution and frame rate are the most critical metrics determining the tracking capability and overall data quality of the system. Optical cameras typically capture retroreflective markers that are 10 to 15 mm in diameter, and data can only be generated when a marker occupies a specific number of pixels on the camera sensor. Consequently, higher resolution allows the camera to distinguish markers from a greater distance, significantly improving data precision. Along with resolution, the frame rate dictates how many times the camera captures images per second. A higher frame rate plays a vital role in capturing fast and dynamic movements—such as an athlete's pitching motion or a high-speed robot—smoothly and accurately without motion blur or latency.
As the capture space gets larger, selecting high-resolution cameras and planning precise layouts become crucial. Since higher camera resolution increases the maximum marker recognition distance and enhances data precision, high-resolution cameras are much more suitable for covering large volumes. While it is technically possible to increase the marker size to extend the recognition distance, this is not recommended as it can negatively impact data accuracy. Therefore, to maintain high data quality in a large space, the ideal solution is to invest in high-resolution cameras rather than adjusting marker sizes, and to determine the optimal number and placement of cameras so that markers are adequately captured within the field of view of multiple cameras.