Image-Based Acoustic Feature Estimation for Indoor Spaces
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Solution Overview
Problem
Existing techniques for acquiring acoustic features of indoor spaces, such as those used in augmented reality devices, require dedicated equipment, making it difficult to easily and efficiently estimate these features for users who move between different rooms.
Innovation Solution
An acoustic feature estimation method that utilizes image data and machine learning to determine provisional acoustic values, which are then corrected based on room size and object information, allowing for accurate estimation without dedicated equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated equipment such as measuring microphone arrays or measuring speaker arrays are used to acquire acoustic features, then measurement precision is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent uses image data (visual copy) to estimate acoustic features instead of using actual acoustic measurement equipment. The system captures images of the indoor space, extracts material information and spatial characteristics from these images, and uses this visual information to estimate acoustic properties like reverberation time and sound absorption coefficients, thereby avoiding the need for dedicated acoustic measurement devices
Solution Approach 2:
The patent replaces the mechanical/acoustic measurement system (microphone arrays, speaker arrays) with an optical system (imaging devices). Instead of using sound waves to measure acoustic properties, the system uses light-based imaging to capture spatial and material information, then processes this visual data to estimate acoustic features through computational methods
2Measurement precision
If dedicated equipment is used to acquire acoustic features, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system uses readily available image data to estimate acoustic features, replacing complex acoustic measurement procedures with simple image capture and processing. Users can obtain acoustic feature estimates by taking photos or using existing images, which is much easier than setting up and operating specialized acoustic measurement equipment
Solution Approach 2:
The system enables automatic estimation of acoustic features from image data without requiring user expertise in acoustic measurement. The image processing and acoustic feature estimation are performed automatically by the system, making the process accessible to ordinary users who would otherwise be unable to conduct acoustic measurements
3Adaptability or versatility
If acoustic features are acquired for multiple indoor spaces, then adaptability is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary estimation of acoustic features using image data before actual acoustic measurements are needed. By pre-processing image information to extract material properties and spatial characteristics, the system prepares acoustic feature estimates in advance, reducing the time required when multiple spaces need to be evaluated
Solution Approach 2:
The system uses a universal image-based approach that can estimate acoustic features for various types of indoor spaces without requiring different measurement equipment or procedures. The same image processing pipeline works for different room types, materials, and configurations, enabling rapid adaptation to multiple spaces with a single methodology
Data Source
AI summary
An acoustic feature estimation method is an acoustic feature estimation method for estimating an acoustic feature of a space and includes acquiring data on the space, estimating situations in the space in accordance with the acquired data, correcting a provisional value of the acoustic feature in accordance with the estimated circumstances, and outputting the corrected provisional value.