Emergency Vehicle Detection Using Sound-Image Correlation
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Solution Overview
Problem
Existing methods for detecting the location of emergency vehicles face accuracy issues when relying solely on sound or image, with latency problems in sound-based detection and misidentification in image-based detection.
Innovation Solution
A method and device that utilize both sound and image data to detect emergency vehicles, employing neural networks for spectrogram analysis and Gaussian function correlation to enhance accuracy, incorporating self-supervised learning for improved location detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If emergency vehicle location is detected based on sound, then detection speed is improved, but accuracy decreases due to latency issues
Solution Approach 1:
The patent combines sound-based detection and image-based detection into a unified system that processes both modalities simultaneously. The sound detection provides rapid initial localization while image processing confirms vehicle identity and refines location accuracy, eliminating the latency problem of sound-only methods.
Solution Approach 2:
The patent introduces an intermediary correlation analysis mechanism that bridges sound-based and image-based detection results. By analyzing the correlation between sound source location and image-identified vehicle location, the system resolves latency discrepancies and achieves accurate emergency vehicle detection.
2Measurement precision
If emergency vehicle location is detected based on images, then location precision is improved, but accuracy of detecting whether there is an emergency vehicle decreases
Solution Approach 1:
The patent merges image-based location precision with sound-based emergency vehicle identification. While images provide precise location data, sound analysis (particularly siren detection) confirms the presence of an emergency vehicle, together achieving both precision and reliability.
Solution Approach 2:
The patent uses correlation analysis as an intermediary to validate whether an image-detected vehicle is an emergency vehicle. By cross-referencing image location with sound source location and emergency vehicle sound characteristics, the system accurately determines if the detected vehicle is indeed an emergency vehicle.
3Measurement precision
If both sound and image data are processed, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the detection system into distinct modules: sound acquisition and processing, image acquisition and processing, and correlation analysis. This modular segmentation manages complexity by allowing each component to be optimized independently while working together to achieve high detection accuracy.
Solution Approach 2:
The patent implements a multi-functional detection system where the same processing framework handles both sound and image data. The correlation analysis mechanism serves multiple purposes: validating emergency vehicle detection, refining location accuracy, and reducing false positives, thereby managing complexity through universal processing principles.
Data Source
AI summary
An emergency vehicle detection method includes acquiring, by an acquisition device, sounds of external vehicles including an emergency vehicle and a general vehicle; generating, by a generator, a first spectrogram for an emergency vehicle sound and a second spectrogram for a general vehicle sound; generating, by the generator, first emergency vehicle location information based on the first spectrogram; generating, by the generator, general vehicle location information based on the second spectrogram; acquiring, by the acquisition device, images of the external vehicles; generating, by the generator, second emergency vehicle location information based on the images of the external vehicles; and detecting, by a detector, a location of the emergency vehicle based on a correlation of at least two of the first emergency vehicle location information, the general vehicle location information, or the second emergency vehicle location information.