Projects:Improve tracking of individual markers and marker patterns

Overview

• Input : Tracking data in .csv format (Tracker, Nexus), 3D backpack points, detected single marker points
• Output : Combine the datasets, fill in gaps where only some but not all makers of the full pattern is detected, and filter random flips in output from Nexus

Subprojects: 2.1 Offline data processing; 2.2 Online/quasi-real time solution working from the data stream

Contact

• Mate Nagy, mnagy@orn.mpg.de
• Hemal Naik, hnaik@orn.mpg.de

Aims

List the aims of your project, or what you expect anyone taking up the project is supposed to hopefully achieve. The more specific, the better.

Estimated level of difficulty

If you have an estimate, classify level of difficulty according to the description of the CCU in the cluster proposal into

• Standard problems which just require applying existing methods (Hiwi level)
• Elaborate problems which require substantial adaptation or extension of existing methods (Master student level)
• Special problems which require research of entirely new methods and might lead to a paper or two (Ph.D. student level)

Maybe add a short clarification of what you believe are the main difficulties, and why you believe this is the right classification.

Provided data

See Vicon:Data format documentation.

Suggested/tested approaches

• Possible approach:

A. Backpack points can be transferred to coordinate system of VICON using output of tracker (6DOF pose transformation between VICON and Backpack coordinate system). Tracker has better optimization techniques than nexus therefore trajectories are more complete. The result is compared with 3D points given by Nexus and a combined dataset can be created. B. Results from A is compared with .csv of unlabeled points (Tracker output of 3D all detections) to label all detected 3D points and remove ghost points. C. The combined result from A and B can be used then to identify random flips in angles, positions and IDs.