Depth-Based Visual Search Area for Lower-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
Selecting 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 comprehensive information can be obtained, but computational cost increases significantly
Solution Approach 1:
The patent divides the image processing task into two segments: first processing a depth map to identify a search area, then processing only that specific region in the color image. This segmentation reduces the amount of data requiring intensive computational processing while ensuring relevant information is extracted.
Solution Approach 2:
The patent applies different processing quality and intensity to different regions of the image. The identified search area receives full processing attention for information extraction, while the rest of the image receives minimal or no processing, optimizing computational resource allocation based on local importance.
2Loss of information
If the entire image is processed for information extraction, then all potential information is captured, but processing time increases
Solution Approach 1:
The patent segments the processing workflow into rapid depth map analysis followed by targeted color image processing of only the relevant search area. This approach significantly reduces total processing time compared to analyzing the entire color image, while maintaining information extraction completeness within the area of interest.
Solution Approach 2:
The patent performs preliminary processing of the depth map to identify the search area before processing the color image. This preliminary action enables subsequent focused processing, reducing overall processing time while ensuring no relevant information is missed in the final extraction phase.
3Device complexity
If a fixed search area is used, then processing is simplified, but adaptability to different scenarios is reduced
Solution Approach 1:
The patent implements a dynamic search area determination mechanism that adapts to different scenarios. The system calculates the search area based on depth information and adjusts its boundaries according to the specific context, maintaining low complexity through algorithmic adaptability rather than multiple fixed configurations.
Solution Approach 2:
The patent changes the parameters defining the search area (position, size, shape) based on depth map analysis and scene characteristics. This allows the system to adapt to different scenarios by modifying search area parameters dynamically, balancing processing simplicity with scenario-specific adaptability.
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.