Retinal Implant Visual Cueing for Clutter Reduction
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Solution Overview
Problem
Retinal implant systems like the ARGUS II face challenges in identifying objects and faces in cluttered environments due to limited electrode arrays and high-frequency spatial information, making it difficult for visually impaired individuals to navigate and interact with their surroundings effectively.
Innovation Solution
The implementation of clustering algorithms such as K-Means and Mean Shift, combined with contrast enhancement techniques, to process images and reduce clutter, allowing for improved object and face detection, and the provision of spatial cues to guide the user in centering objects of interest within the limited implant field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If clustering algorithms and contrast enhancement techniques are applied to process images, then object and face detection accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The image processing pipeline is divided into distinct sequential stages: clustering algorithms (K-Means, Mean Shift) for clutter reduction, contrast enhancement techniques, and object/face detection. Each stage processes and refines the data from the previous stage, allowing complex computations to be broken down into manageable segments that can be executed efficiently on embedded platforms.
Solution Approach 2:
Clustering algorithms are applied preliminarily to reduce clutter and simplify the image before object and face detection occurs. By performing clutter reduction in advance, the subsequent detection algorithms operate on a simplified dataset, reducing their computational burden while maintaining high detection accuracy.
2Productivity
If real-time processing at 30 frames per second is implemented, then responsiveness is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic processing at 30 frames per second, where image processing operations are executed in periodic cycles. This structured periodic execution allows for optimized memory access patterns and computational scheduling, achieving real-time responsiveness while managing energy consumption through efficient periodic operation rather than continuous processing.
Solution Approach 2:
The system dynamically adjusts processing parameters based on scene complexity and detected objects. When clutter is detected, clustering algorithms are applied with adjusted parameters to reduce computational load. The contrast enhancement and detection algorithms modify their processing intensity based on the simplified image data, achieving 30 fps performance while optimizing energy usage through adaptive parameter modification.
3Device complexity
If the implant field of view is made smaller to match the electrode array, then device complexity is reduced, but the ability to capture comprehensive environmental information is worsened
Solution Approach 1:
The system extracts and processes only the most salient information from the full camera field of view. Clustering algorithms identify and extract dominant color regions and objects, while contrast enhancement techniques highlight salient features. This extracted and enhanced information is then presented to the user, effectively compensating for the limited implant field of view by concentrating computational resources on the most important environmental elements rather than processing the entire scene uniformly.
Data Source
AI summary
An apparatus for improving performance of a retinal implant may include processing circuitry. The processing circuitry may be configured to receive image data corresponding to a camera field of view, determine whether a particular object is detected within the camera field of view, perform image data processing to enable a representation of a portion of the image data corresponding to an implant field of view to be provided on a retinal implant where the implant field of view is smaller than the camera field of view, and, responsive to the particular object being located outside the implant field of view, provide a directional indicator in the implant field of view to indicate a location of the particular object relative to the implant field of view.