Vision Enhancement Apparatus Depth Processing
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Solution Overview
Problem
Vision-impaired individuals face challenges in navigating their environment due to partial sight conditions such as cataracts, retinitis pigmentosa, and age-related macular degeneration, which limit their field of vision and make it difficult to detect obstacles or objects in real-time.
Innovation Solution
A vision enhancement apparatus comprising a passive sensor to acquire high-resolution video data, a sight processor to analyze and extract depth of field information, and a visual display system to present this information to the user through interface equipment, such as bionic eyes, retinal implants, or vision spectacles, providing real-time depth cues and hazard warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution video data is processed to provide detailed visual information, then the quality of artificial vision is improved, but the processing time and complexity increase
Solution Approach 1:
The patent divides the visual field into multiple depth zones (near, mid, far) and processes each zone separately with appropriate resolution levels. This segmentation allows the system to provide accurate depth information for critical near objects while using lower resolution for distant areas, maintaining real-time performance while improving where needed.
Solution Approach 2:
The system extracts only the essential depth of field information from the full high-resolution video data using automated image analysis. By extracting specifically the depth metrics needed for navigation rather than processing all visual details, the system achieves accurate depth perception with reduced processing time.
2Area of stationary object
If the field of view is expanded to detect more obstacles, then the safety is improved, but the resolution of each detected object decreases
Solution Approach 1:
The patent applies different quality levels to different regions of the visual field. Critical areas such as the central field and areas with detected obstacles receive high-resolution processing, while peripheral areas use lower resolution. This local quality approach ensures safe navigation with comprehensive coverage without uniformly sacrificing detail.
Solution Approach 2:
The system adds a depth dimension to the visual information by providing depth of field data alongside 2D image data. This third dimension allows the user to perceive distance and spatial relationships even when object detail is reduced, maintaining detection accuracy across a wider field of view.
3Reliability
If multiple sensors are used to capture comprehensive visual data, then the reliability of obstacle detection is improved, but the device complexity increases
Solution Approach 1:
The patent designs the sensor system so that a single camera can perform multiple functions: capturing 2D images for object identification, extracting depth information through image analysis, and providing wide-field coverage for obstacle detection. This multi-functionality achieves reliable detection without requiring multiple specialized sensors.
Solution Approach 2:
The system uses an automated image analysis processor as an intermediary that extracts depth of field information from standard video data. This intermediary processing layer enables comprehensive multi-dimensional detection using conventional sensors, avoiding the need for complex specialized hardware while maintaining high reliability.
Data Source
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AI summary
This invention concerns a vision enhancement apparatus that improves vision for a vision-impaired user of interface equipment. Interface equipment stimulates the user's cortex, directly or indirectly, to provide artificial vision. It may include a passive sensor to acquire real-time high resolution video data representing the vicinity of the user. A sight processor to receive the acquired high resolution data and automatically: Analyse the high resolution data to extract depth of field information concerning objects of interest. Extract lower resolution data representing the vicinity of the user. And, provide both the depth of field information concerning objects of interest and the lower resolution data representing the vicinity of the user to the interface equipment to stimulate artificial vision for the user.