29 Nov 2023
A marker set is far more than the floating points recorded in a capture space. Curating a full marker set in Cortex is an integral stage to define the markers’ properties, and their relation to each other, in order to develop a model that can be used for a range of motion capture studies. Marker sets need to be identified to drive underlying skeletons that can be reused or modified in live mode or during post-processing.
We run through the various components of a Cortex “MarkerSet” and how to construct them to best suit your motion capture research and project needs for biomechanics, clinical trials, gait analysis, and character animation.
MarkerSet components can be found and edited in the right-hand panel of the Cortex platform, titled Properties, before being saved and exported in a comprehensive marker set file. The listed MarkerSet properties are as follows:
Markers are small points attached to a test subject and tracked by cameras to capture movement. When displayed as raw data in Cortex, these markers are unnamed, but you can name them based on their positions on the body to identify them easily.
Virtual markers define central locations where ‘real’ markers cannot be placed—the middle of a joint, for example. Virtual markers can calculate a location relative to up to three ‘real’ markers or other virtual markers, which is very useful when needing to define the endpoints of a segment.
Segments represent different portions of the body. Each segment’s movement is driven by the positions of identified markers, which can calculate its rotation across three axes. Segments can be automatically adjusted, or you can manipulate segments saved in the MarkerSet to fit various motion capture subjects.
Links “connect the dots” between markers to map their relative distance. Each link has an allowable distance (how close or far the markers can be to each other) where markers outside of this range cannot be identified. Links are critical to the real-time identification process, where you can elongate or shorten links to fit different test subjects, and they allow you to identify markers during the post-processing stage using templating tools.
Rigid Subsets can be created using markers that do not move relative to each other, such as those on a rigid plate attached to a test subject. When a subject is first in the capture space, Cortex first tries to identify the rigid subsets in the MarkerSet before the other markers. This adds another layer of accuracy for identification either during live mode or post-process.
The Template allows you to automatically assign the identified markers from one MarkerSet to the raw data’s unnamed points in one go. This part of a MarkerSet also allows you to select a repeatable Model Pose—a “standard position” that can be chosen from a single captured frame that visualizes identified markers.
For biomechanics motion capture research or clinical analysis, more detailed markers are needed to drag the underlying skeleton and gain precise data to construct the MarkerSet.
Markers should be placed on accurate anatomical locations throughout the body based on which physical activity is being evaluated. Studying baseball pitching would require detailed markers on the upper extremities, whereas running or jumping activities may require more markers on the lower extremities. Either way, the marker positions drive the movement of the segments. Without identifying these markers, it’s impossible to work out joint kinematics and the subsequent kinetics for the skeleton.
Biomechanical work utilizes the Skeleton Builder engine (SkB) to accurately define the movement of every segment. You need at least three markers on a segment (real, virtual, or combinations of both) in order to calculate rotation using a three-point axis. This 3D coordinate system helps to assess limb movements including joint flexion/extension, abduction/adduction, and internal/external rotations.
Animation generally relies on the same anatomical marker locations as above, but accuracy is not as crucial. For character animators, it is important that the resulting skeleton mimics the actor’s movements as best as possible, and every segment identified in Cortex’s MarkerSet has to match the animated character it is driving.
Animators use the Calcium Solver in Cortex, which defines segments differently and more flexibly. This software uses a globally optimized solution to drive an underlying skeleton rather than using three fixed marker points, and utilizes joint types and limitations to constrain the skeleton movement. Each segment is attached to a marker with an attachment. These attachments act like springs, telling the software which markers are driving the motion so that related segments can move in a similar way. This solution allows you to control the full skeleton according to these segment preferences determined in the MarkerSets.
The hybrid skeleton builder is also useful for creating a MarkerSet in that it combines the functionality of the two engines listed above. For the initial stage, it offers the scalability options offered by the SkB engine, but completes the remainder of the process using Calcium’s globally optimized solution to define a subject’s dynamic movements.
Cortex displays all the MarkerSet information upfront, allowing you define its properties as you see fit, with file names, marker names and even links colors being fully customizable.
Once all of a MarkerSet’s components are saved, the resulting template can be viewed during post-processing or be loaded into a live capture and tweaked accordingly to fit different motion capture subjects. Using a defined marker set as the first port of call, motion capture research and analysis can be conducted faster, with marker sets fully adaptable for your specific industry use case.
If you’re inspired to collate your own marker set for a particular motion capture project or if you’d like more info, feel free to reach out to our team today.