Depth-Based Visual Search Area for Low-Cost Image Extraction
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Solution Overview
Problem
Extracting information from entire images using electronic devices with cameras is computationally expensive.
Innovation Solution
Select a portion of the image based on the user's gaze location and distance to an object in the physical environment for processing, reducing computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If information extraction is performed on the entire image, then complete information can be obtained, but computational cost increases
Solution Approach 1:
The patent segments the image processing task by dividing it into two stages: first processing a depth map to identify a search area, then processing only that specific region in the color image. This segmentation allows complete information extraction from relevant areas while avoiding unnecessary computation on irrelevant portions of the full image.
Solution Approach 2:
The patent extracts and processes only the relevant portion of the image (the search area) rather than the entire image. By taking out the specific region containing the object of interest based on depth information, the system maintains information extraction effectiveness while significantly reducing computational cost.
2Productivity
If the field-of-view is reduced to a specific area, then computational load decreases, but coverage of the environment is limited
Solution Approach 1:
The patent introduces depth information as an additional dimension to guide the selection of the search area. By using the depth map to identify regions at specific distance ranges, the system dynamically determines the field-of-view based on three-dimensional spatial information, ensuring efficient processing while maintaining appropriate environmental coverage.
Data Source
AI summary
In one implementation, a method of extracting information from a physical environment is performed at a device including an image sensor, one or more processors, and non-transitory memory. The method includes determining a gaze location and a distance to an object in a physical environment at the gaze location. The method includes selecting a field-of-view of the physical environment based on the gaze location and the distance to the object. The method includes obtaining, using the image sensor, an image corresponding to the field-of-view of the physical environment. The method includes extracting information from the image.