Smart Prosthesis Scene Abstraction for Visual Task Assistance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing retinal prostheses have low bandwidth and pixel resolution, making them ineffective for assisting visually impaired users in everyday tasks due to dominance of irrelevant idiosyncratic information in pixel intensities.
Innovation Solution
A smart prosthesis system that extracts high-level abstracted information from camera and sensor data using advanced computational techniques to produce a simplified, abstracted representation of the visual world, optimized for specific tasks such as navigation, reading, and shopping, using a processor and Internet-connected device to stimulate the retina.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If standard image processing techniques are used on pixel values from imaging cameras, then the processing is simple and fast, but the visual information remains dominated by irrelevant idiosyncratic information that does not help visually-impaired users perform tasks
Solution Approach 1:
The patent extracts task-relevant information from the visual scene by identifying and isolating specific features such as edges, corners, and salient objects. This extraction process removes irrelevant idiosyncratic pixel information while retaining only the essential visual cues needed for tasks like navigation and object recognition, thereby resolving the contradiction between information quality and processing complexity.
Solution Approach 2:
The system transforms the representation of visual information from raw pixel intensities to abstracted feature descriptors. By changing the parameters from pixel-level data to higher-level semantic features, the system eliminates irrelevant information while maintaining task-relevant content, achieving both information quality improvement and manageable complexity through the use of specialized processing algorithms.
2Measurement precision
If raw or filtered pixel camera video is relayed to the user, then the system is simple to operate, but the low bandwidth and pixel resolution make the information unintelligible and useless for everyday tasks
Solution Approach 1:
The patent segments the visual scene into meaningful components such as foreground objects, background elements, and spatial relationships. By dividing the complex visual information into discrete, task-relevant segments, the system enhances information quality for low-resolution displays while keeping processing complexity manageable through modular analysis of different scene elements.
Solution Approach 2:
The system transitions from two-dimensional pixel representations to a multi-dimensional feature space that includes spatial, semantic, and contextual dimensions. This dimensional transformation allows the system to convey richer visual information quality despite the constraints of low bandwidth and resolution, while the structured approach to dimensionality management keeps processing complexity controlled.
3Loss of information
If advanced computational techniques are used to extract high-level abstracted information in real-time, then task-relevant information quality is improved, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent applies preliminary processing steps such as edge detection, feature extraction, and scene segmentation before final image generation. By performing these computational tasks in advance and caching intermediate results, the system achieves high-quality task-relevant information extraction while reducing the real-time computational burden, thus resolving the contradiction between information quality and processing complexity.
Data Source
AI summary
A method of providing artificial vision to a visually-impaired user implanted with a visual prosthesis. The method includes configuring, in response to selection information received from the user, a smart prosthesis to perform at least one function of a plurality of functions in order to facilitate performance of a visual task. The method further includes extracting, from an input image signal generated in response to optical input representative of a scene, item information relating to at least one item within the scene relevant to the visual task. The smart prosthesis then generates image data corresponding to an abstract representation of the scene wherein the abstract representation includes a representation of the at least one item. Pixel information based upon the image data is then provided to the visual prosthesis.