UWB-Augmented Camera Tracking for Occluded Subject Identification
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Solution Overview
Problem
Conventional entity detection in imaging systems fails to identify and track entities under poor lighting conditions or when entities are occluded, leading to inferior performance in camera autofocusing and auto framing.
Innovation Solution
The use of ultra-wideband (UWB) communication with tags attached to entities allows for accurate identification and tracking by determining their position within the camera's field of view, even in occluded conditions, using time of flight and angle of arrival calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional entity detection processes are used that rely on image/video data analysis, then the system can identify entities under normal conditions, but the system fails to identify entities under poor lighting conditions or when entities are occluded
Solution Approach 1:
The patent introduces positioning tags as intermediary devices that attach to entities. These tags emit signals that the imaging system can detect independently of lighting conditions or occlusion. The tags serve as mediators between the entity and the detection system, providing reliable position and identity information even when visual detection fails.
Solution Approach 2:
The patent replaces the optical-based detection mechanism (which relies on light reflection and image analysis) with a radio frequency-based detection mechanism using UWB tags. This substitution allows the system to detect entities through electromagnetic signals that are not affected by lighting conditions or visual occlusion, fundamentally changing how entity detection is performed.
2Measurement precision
If the system uses positioning tags with UWB communication for entity identification, then entity tracking accuracy improves under poor lighting and occluded conditions, but the device complexity increases
Solution Approach 1:
The positioning tags are designed to perform multiple functions: they store entity identity information, provide precise position data through UWB communication, and enable both detection and tracking capabilities. This multi-functionality reduces the need for separate systems for each function, thereby managing complexity while achieving high measurement precision.
Solution Approach 2:
The system utilizes UWB technology which operates on specific electromagnetic frequency parameters that allow for high precision time of flight measurements. By changing to this specific frequency band and measurement approach, the system achieves centimeter-level position accuracy without requiring complex mechanical or optical systems.
3Productivity
If conventional contrast detection and pattern recognition are used, then the system can identify entities with simple processing, but the system performance deteriorates when entities are not visible in the field of view
Solution Approach 1:
The system performs preliminary detection using UWB tags to identify entity positions and identities before attempting visual detection. This preliminary action provides the system with advance information about entity locations, allowing it to maintain tracking even when visual detection fails, thereby improving both reliability and overall detection efficiency.
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
This approach effectively identifies and tracks entities in images/video data under poor lighting conditions and when entities are occluded, improving camera autofocusing and auto framing capabilities.
Implementation Method 1
determining their position within the camera's field of view, even in occluded conditions, using time of flight and angle of arrival calculations
Implementation Method 2
determining their position within the camera's field of view, even in occluded conditions, using time of flight and angle of arrival calculations
Data Source
AI summary
A camera system may determine positions of one or more candidate subjects in the camera view of at least one camera, wherein each candidate subject is associated with a positioning tag that stores an identity of the candidate subject. A camera system may receive identities of the one or more candidate subjects from the positioning tags. A camera system may match an identity of the tracked subject to an identity of a particular candidate subject of the one or more candidate subjects. A camera system may adjust camera operation of the at least one camera corresponding to a determined position of the positioning tag of the particular candidate subject relative to the at least one camera.