3D Object Position Tracking With Asynchronous Multi-Camera Views
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Solution Overview
Problem
Current systems for determining the position of objects in real-life scenes require synchronized cameras and a minimum of two cameras to see the object, limiting camera variety and being difficult to implement due to occlusion issues, especially in sports events.
Innovation Solution
A method using a device that obtains images from multiple cameras with different fields of view, builds a 3D model of the object's position over a time window, and establishes its real-world position by triangulation, even with asynchronous camera synchronization, utilizing physiological constraints and 3D modeling software to optimize object tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If synchronized cameras are used to determine object position, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system dynamically adjusts the time window for collecting images from multiple cameras, allowing flexible adaptation to different scene conditions and object movement speeds without requiring rigid synchronization, thereby reducing system complexity while maintaining position detection accuracy
Solution Approach 2:
The patent changes the parameter of time synchronization from strict simultaneous capture to a flexible time window approach, where images from multiple cameras are collected within a defined time range rather than requiring exact synchronization, simplifying the camera system architecture
2Measurement precision
If a minimum of two cameras are required to see the object, then measurement precision is improved, but reliability deteriorates due to occlusion
Solution Approach 1:
The system collects images from more than the minimum two cameras by utilizing all available cameras within the time window, allowing sufficient data for position calculation even when some cameras have occluded views of the object
Solution Approach 2:
The patent introduces a time window as an intermediary mechanism that collects images from multiple cameras at different times, allowing the system to overcome occlusion by gathering sufficient viewing angles across the time period rather than requiring simultaneous multi-camera coverage
3Measurement precision
If synchronized camera systems are implemented, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically processes images from multiple cameras within the defined time window without requiring manual synchronization configuration, with the processor autonomously selecting and processing suitable images based on object detection and time-stamping
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and efficient detection of object positions in real-world scenes with diverse camera setups, reducing the need for complex synchronization and overcoming occlusion challenges, allowing real-time decision support in sports and other applications.
Implementation Method 1
building a 3D model of the continuous real-world position of the object in the real-world scene over the first time window based upon the determined position in each image captured by the plurality of cameras
Data Source
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AI summary
A method of detecting the real-world position of an object in a real-world scene, comprising: obtaining, from a plurality of cameras each having a different field of view of the object, a plurality of images of the object in the real-world scene over a first time window, each of the plurality of images being provided by a different one of the cameras; determining the position of the object in each image captured by each of the plurality of cameras over the first time window; building a 3D model of the continuous real-world position of the object in the real-world scene over the first time window based upon the determined position in each image captured by the plurality of cameras; and establishing, from the 3D model, the 3D position of the object at a particular time in the real-world scene.