Camera Microphone Array FOV-Based Audio Selection
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Solution Overview
Problem
Conventional security camera systems struggle with noise and reflection issues in environments with multiple noise sources, as they capture audio from all directions without considering the camera's field of view (FOV), leading to poor audio quality.
Innovation Solution
The system uses sensor data from accelerometers and gyroscopes to determine the camera's FOV and selectively activate a subset of microphones for audio beamforming, focusing on sound within the current FOV and attenuating noise from outside areas, ensuring cleaner audio recordings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If all microphones are activated to capture audio, then audio coverage is comprehensive, but noise and reflections from outside the field of view are included
Solution Approach 1:
The system segments the microphone array into multiple zones corresponding to different spatial regions. Each microphone is assigned to a specific zone, and only microphones in the current field of view zone are activated. This segmentation allows the system to capture audio selectively from relevant areas while excluding noise from other regions.
Solution Approach 2:
The system dynamically adjusts which microphones are activated based on the current field of view direction. As the camera pans or tilts, the system updates the active microphone subset to match the new FOV orientation. This dynamic adaptation ensures that audio capture always corresponds to the current visual field while maintaining comprehensive coverage as the camera moves.
2Measurement precision
If microphones are selected based on field of view, then audio quality within FOV is improved, but audio capture outside FOV is lost
Solution Approach 1:
The system performs preliminary identification of the field of view direction using sensor data from accelerometers and gyroscopes before activating microphones. By determining the current FOV orientation in advance, the system can pre-select the appropriate subset of microphones that will capture audio within the FOV, ensuring high audio quality from the start without losing relevant information.
Solution Approach 2:
The system continuously monitors sensor data from accelerometers and gyroscopes to track changes in camera orientation. Based on this feedback, the system dynamically updates which microphones are active to maintain alignment between the audio capture zone and the visual field of view. This feedback loop ensures that audio quality within the FOV is optimized while capturing all relevant audio events.
Data Source
AI summary
Systems and methods are described for improving audio quality. Sensor data is received from an accelerometer of a camera. Based on measurements captured by the sensor data, a position of a lens of the camera and a current field of view (FOV) of the camera is determined. Audio beamforming is performed based on the current FOV of the camera by selecting a subset of microphones disposed on the camera to record audio based on the position of the lens and the current FOV of the camera; and activating the subset of microphones disposed on the camera, where microphones outside the selected subset of microphones are excluded from activation so that audio originating outside of the current FOV is removed.