Photon Signature Classification for Low-Light Object Detection
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Solution Overview
Problem
Existing visual object detection and classification systems face challenges in low lighting conditions, slow computation speeds, high power consumption, and privacy concerns, particularly in scenarios where capturing detailed images is undesirable or impossible.
Innovation Solution
A computing system utilizing a photon detection system with photon detectors that output photon signatures, combined with a low-photon-count classification model, allows for rapid and accurate object classification by incrementally updating a classification evidence vector with each photon signature, stabilizing the classification before a comprehensive image is captured.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image capture and processing methods are used, then comprehensive visual information is obtained, but photon consumption is high and processing time is long
Solution Approach 1:
The patent extracts only the essential visual information needed for classification by processing photons incrementally as they arrive, rather than capturing complete images. The system extracts classification-relevant features from photon signatures in real-time, discarding redundant spatial and temporal information that would require full image capture.
Solution Approach 2:
The system performs preliminary classification actions before complete image data is available. By maintaining running statistics and updating classification evidence incrementally as photons arrive, the system can reach classification decisions with far fewer photons than traditional methods require.
2Measurement precision
If conventional image processing is used, then detailed object information is captured, but computation speed is slow
Solution Approach 1:
The patent segments the image processing task into incremental updates based on individual photon arrivals. Instead of processing complete images, the system divides classification into discrete steps where each photon signature contributes incrementally to the final classification decision, enabling real-time processing.
Solution Approach 2:
The system replaces mechanical image capture and processing with a computational model that directly processes photon signatures. By substituting physical image formation with statistical processing of photon arrival data, the system achieves faster computation without sacrificing classification accuracy.
3Measurement precision
If comprehensive image capture is performed, then complete visual data is obtained, but power consumption is high
Solution Approach 1:
The system applies partial action by processing only the minimum necessary photon data for classification. Rather than capturing and processing complete images, the system uses partial image information from incremental photon arrivals, achieving sufficient classification accuracy with reduced energy expenditure.
4Measurement precision
If detailed images are captured for classification, then comprehensive object information is obtained, but privacy concerns increase
Solution Approach 1:
The patent extracts only classification-relevant information from photon data without capturing complete images that would reveal private details. By processing photons incrementally and making classification decisions before full image formation, the system avoids creating detailed visual records that could infringe privacy.
Solution Approach 2:
The system uses photon signatures as an intermediary representation between the visual scene and classification output. This intermediary form contains sufficient information for classification while inherently limiting the ability to reconstruct detailed images, thus protecting privacy while maintaining classification accuracy.
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 object classification with reduced photon counts, faster processing times, and lower power consumption, suitable for low-light and privacy-sensitive applications.
Implementation Method 1
Each of the one or more photon detectors can be configured to output photon signatures in response to a photon being incident on the one or more photon detectors
Data Source
AI summary
A computing system can be configured for low-photon-count visual object classification. The computing system can include a photon detection system including one or more cells. Each of the one or more cells can include one or more photon detectors. Each of the one or more photon detectors can be configured to output photon signatures in response to a photon being incident on the one or more photon detectors. The computing system can include one or more processors and one or more memory devices storing computer-readable data. The data can include a low-photon-count classification model and one or more instructions that, when implemented, cause the one or more processors to perform operations for low-photon-count visual object recognition. The operations can include obtaining a photon signature from a photon detection system. The operations can include providing the photon signature to a low-photon-count classification model. The operations can include determining, by the low-photon-count classification model, a classification of a visual object disposed in view of the photon detection system based at least in part on the photon signature. The operations can include providing the classification as output of the low-photon-count classification model.