
TL;DR
This paper introduces a theoretical framework for integrating existing real-time optical tracking systems with user identification and activity history features, addressing challenges like data fusion without direct system communication.
Contribution
It presents a novel method to fuse tracking data with user identification and history, without requiring direct communication with the tracking system.
Findings
Framework effectively integrates tracking data with user IDs and history.
Method handles unordered and variable number of tracked objects.
Enables seamless transition between different tracking modalities.
Abstract
The issue of seamless identification of users previously tracked using existing real-time optical position tracking system such as the OptiTrack system and maintaining continuous tracking state (history) of each of those users is a hard problem. In this article, we present a theoretical framework to integrate existing tracking systems with features such as user identification and history of up to `n' person activity. In our approach, we assume no direct communication with the tracking system, but access to all data it collects. Also, there are no guarantees that 1) the order of each tracked retro-reflective sphere reported is the same, and 2) that there will be any particular number of spheres in the room at any given time. We describe how the data is fused with existing tracking data to provide a seamless transition between other forms of position tracking.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Gaze Tracking and Assistive Technology · Interactive and Immersive Displays
