Video Camera Audio Pre-Analysis Filter for Real-Time Event Detection
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Solution Overview
Problem
Complex sound classification algorithms used in video cameras for automatic event detection are computationally intensive, making them unsuitable for real-time analysis on audio devices, as they require significant processing time, which is not feasible for timely alert triggering.
Innovation Solution
Implementing pre-analysis filters in video cameras to quickly identify predetermined features of interest in audio data, allowing only relevant data to be processed by complex models, thereby reducing computational load and enabling faster analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex sound classification algorithms are used for event detection, then detection accuracy is improved, but processing time increases making real-time analysis infeasible
Solution Approach 1:
The audio processing system is segmented into multiple stages: initial filtering stage and detailed analysis stage. The pre-analysis filter segments the audio data processing from the complex classification algorithm, allowing only relevant segments (audio chunks containing predetermined features) to undergo full analysis, thus reducing overall processing time while maintaining detection accuracy
Solution Approach 2:
A pre-analysis filter is applied preliminarily to audio data before it undergoes complex classification. This preliminary action identifies and flags audio chunks containing predetermined features of interest (e.g., gunshot, glass breaking patterns), preparing them for subsequent detailed analysis by the complex algorithm, thereby avoiding unnecessary processing of irrelevant audio data
2Adaptability or versatility
If complex neural networks are used for sound classification, then classification capability is improved, but computational complexity increases beyond what audio devices can handle
Solution Approach 1:
The computationally intensive complex classification algorithm is extracted from the audio device and relocated to a remote server or cloud-based processing system. The audio device retains only the lightweight pre-analysis filter, which extracts and transmits only relevant audio chunks containing predetermined features to the remote system for complex classification, thereby reducing device complexity while preserving classification capability
Solution Approach 2:
A communication interface acts as an intermediary between the audio device and the remote classification system. The pre_analysis filter on the audio device identifies relevant audio data, and this intermediary interface manages the transmission of selected audio chunks to the remote server, which performs the complex neural network classification and returns results, thus distributing computational complexity across multiple systems
Data Source
AI summary
A video camera, a computer-implemented method, and a computer-readable storage medium. The video camera including one or more microphones and a processor. The processor is configured to: acquire an output from the or each microphone; apply one or more pre-analysis filters to the or each acquired output, wherein the or each pre-analysis filter determines if the or each acquired output contains a corresponding predetermined feature of interest; and analyse the or each output, when it is determined by the or each pre-analysis filter that the corresponding output contains at least one predetermined feature of interest.