Correlating 3D Tracking Data with Asynchronous Images
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Solution Overview
Problem
Existing systems fail to effectively correlate high quality images with player identification and biographical information in three-dimensional spaces, especially when data and images are asynchronously captured, limiting the ability to identify players within images and retrieve specific images of individuals in large sporting events.
Innovation Solution
A method that involves attaching remotely-accessible identification tags to individuals and objects, capturing images and tracking data, correlating data by interrelating tag capture times with image capture times, and using camera orientation and location to reduce tracking data to relevant subsets, enabling the identification of players within images and locating all images of a particular player within a three-dimensional space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional identification systems (RFID tags, bar codes) are used to identify people in images, then identification capability is provided, but the system cannot effectively handle large numbers of people in single images or correlate asynchronous images with tracking data in three-dimensional space
Solution Approach 1:
The patent extends traditional 2D image identification to 3D space by incorporating spatial coordinates and camera orientation data. Tracking stations are positioned throughout a three-dimensional space to capture tags from multiple angles and distances, enabling the system to handle large numbers of people and correlate asynchronous images with their spatial context.
Solution Approach 2:
The system divides the identification task into multiple components: tracking stations capture tag data and spatial information, cameras capture images with orientation metadata, and a processor correlates this data by matching tag IDs with image data. This segmentation allows each component to specialize, improving overall capability to handle complex scenarios.
2Ease of operation
If images and tracking data are captured asynchronously by independent systems, then operational flexibility is maintained, but correlation between images and player identification becomes difficult
Solution Approach 1:
The processor continuously receives tracking data and image data from independent sources, correlates them by matching tag IDs with image metadata, and uses this feedback to identify players in images and locate images of specific players. This feedback mechanism enables correlation of asynchronous data without requiring synchronized capture.
Solution Approach 2:
The processor acts as an intermediary that receives data from both tracking stations and cameras, matches tag IDs with image data, and produces correlated results. This intermediary component bridges the independent asynchronous systems, enabling correlation without requiring them to be synchronized.
3Measurement precision
If tracking data from multiple directions and distances is captured, then comprehensive player location information is obtained, but data processing complexity and time increase
Solution Approach 1:
Tracking stations continuously capture tag data, camera location, and orientation in advance, storing this information in a database before image correlation is needed. This preliminary data collection eliminates the need for real-time processing during image analysis, improving processing speed while maintaining comprehensive location information.
Data Source
AI summary
A method for correlating tracking data associated with an activity occurring in a three-dimensional space with images captured within the space comprises the steps of: (a) locating a camera with respect to the three-dimensional space, wherein the camera at a given location has a determinable orientation and field of view that encompasses at least a portion of the space; (b) capturing a plurality of images with the camera and storing data corresponding to the images, including a capture time for each image; (c) capturing tracking data from identification tags attached to the people and/or objects within the space and storing the tracking data, including a tag capture time for each time that a tag is remotely accessed; (d) correlating each image and the tracking data by interrelating tracking data having a tag capture time in substantial correspondence with the capture time of each image, thereby generating track data corresponding to each image; (e) utilizing the track data to determine positions of the people and/or objects within the three dimensional space at the capture time of each image; and (f) utilizing the location and orientation of the camera to determine the portion of the space captured in each image and thereby reduce the track data to a track data subset corresponding to people and/or objects positioned within the portion of space captured in each image.