Multi-Camera Visual Object Recognition Using Segmented Imaging
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Solution Overview
Problem
Current electronic devices face challenges in efficiently recognizing and processing visual objects, such as QR codes, from images captured by cameras, especially when the object is small or at a distance, due to limitations in magnification and image processing capabilities.
Innovation Solution
The electronic device employs a processor to control a display and obtain second frames by adjusting magnification based on distance sensor data, allowing for enhanced image processing and recognition of visual objects, including QR codes, using multiple cameras with overlapping fields of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single camera is used to capture images for visual object recognition, then the device structure remains simple, but the recognition accuracy deteriorates when the object is small or at a distance
Solution Approach 1:
The patent divides the imaging task into multiple segments by using multiple cameras with different fields of view. The first camera captures a wide-area image while the second camera captures a magnified image of a specific region. This segmentation allows the system to achieve both wide coverage and high recognition accuracy without requiring a single complex camera system.
Solution Approach 2:
The patent transitions from a single-view imaging approach to a multi-view imaging approach by adding a second camera with a different field of view. This dimensional change in the imaging system enables the device to capture the same scene from multiple perspectives, improving visual object recognition accuracy particularly for small or distant objects.
2Area of stationary object
If the camera captures a wide-area image to ensure the visual object is within the field of view, then the field of view coverage is improved, but the magnification of the visual object deteriorates
Solution Approach 1:
The patent segments the imaging function into two parts: the first camera provides wide-area coverage to ensure the visual object is within the field of view, while the second camera provides magnified imaging of the specific region containing the visual object. This segmentation resolves the contradiction between wide coverage and high magnification.
Solution Approach 2:
The patent merges the outputs of two cameras with different fields of view by selecting a second region based on the first image and generating a second image that combines the magnified view with the original wide-area context. This merging allows the system to display both wide coverage and high magnification simultaneously.
3Measurement precision
If the camera captures a magnified image to improve visual object recognition, then the recognition accuracy is improved, but the visual object may fall outside the field of view
Solution Approach 1:
The patent performs preliminary action by first capturing a wide-area image with the first camera to identify the region containing the visual object. Based on this preliminary information, the system then captures a magnified image with the second camera targeting the specific region. This preliminary action ensures the visual object remains within the field of view while achieving high magnification.
Solution Approach 2:
The patent implements feedback by using the first image to determine the second region for magnified imaging. The system continuously monitors the first image, identifies the visual object's location, and adjusts the second camera's field of view accordingly. This feedback mechanism ensures the visual object remains within the magnified field of view while maintaining recognition accuracy.
4Measurement precision
If multiple cameras are used to improve visual object recognition, then the recognition accuracy is improved, but the processing complexity deteriorates
Solution Approach 1:
The patent extracts only the necessary processing steps by selectively generating a second image based on the first image and the identified second region. Rather than processing all data from multiple cameras equally, the system extracts and processes only the relevant magnified region, reducing processing complexity while maintaining recognition accuracy.
Solution Approach 2:
The patent applies partial action by processing only the specific second region that contains the visual object rather than the entire wide-area image. This partial processing approach reduces the computational burden while maintaining sufficient information for accurate visual object recognition.
Data Source
AI summary
According to an embodiment, an electronic device includes a plurality of cameras including a first camera and a second camera facing in a same direction as the first camera, a display, a processor, and memory for storing instructions that, when executed by the processor, cause the electronic device to display, on the display, a preview image, based on first image frames obtained using the first camera from among the plurality of cameras. The electronic device includes memory for storing instructions that, when executed by the processor, cause the electronic device to obtain second image frames using the second camera, while displaying the preview image based on the first image frames obtained using the first camera from among the plurality of cameras, based at least in part on determining that a portion of the first image frames includes an object to be recognized.