AR Image Recognition Server Sub-library Segmentation
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Solution Overview
Problem
Augmented reality (AR) devices face increased power consumption and computational burdens due to the need for extensive image recognition processes, leading to heating issues and reduced efficiency as AR scenes become more complex.
Innovation Solution
Implementing a server-based system that generates a picture feature sample sub-library tailored to user information, reducing the amount of data and computations required on the AR device by filtering and pushing only relevant picture feature samples for image recognition, thereby decreasing the computational load and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the AR device performs extensive image recognition processes using a complete picture feature sample library, then image recognition accuracy is improved, but computational burden and power consumption increase
Solution Approach 1:
The complete picture feature sample library is segmented into multiple sub-libraries based on geographic regions. The AR device receives and processes only the sub-library corresponding to its current location, reducing the computational burden while maintaining recognition accuracy for relevant images.
Solution Approach 2:
Different picture feature sub-libraries are provided based on the AR device's geographic location. The system delivers localized picture features relevant to the user's environment, reducing unnecessary computations while maintaining high recognition accuracy for locally relevant images.
2Adaptability or versatility
If the AR device processes a complete picture feature sample library, then image recognition coverage is improved, but device heating increases
Solution Approach 1:
The picture feature sample library is divided into geographic sub-libraries. The AR device processes only the sub-library relevant to its current location, reducing computational load and heat generation while maintaining comprehensive coverage for the user's environment.
Solution Approach 2:
The server pre-processes and segments the complete picture feature library into geographic sub-libraries before transmission. This preliminary segmentation reduces the data volume that the AR device must process, thereby reducing heating while maintaining recognition coverage.
3Speed
If the AR device performs extensive local computations for image recognition, then recognition speed is improved, but computational resources are depleted
Solution Approach 1:
The server extracts and provides only the relevant picture feature sub-library corresponding to the AR device's location, rather than transmitting the complete library. This reduces the computational resources required on the device while maintaining recognition speed through focused processing.
Solution Approach 2:
The picture feature library is segmented by geographic region, allowing the AR device to focus computational resources on processing a smaller, location-specific sub-library, thereby reducing overall computational resource depletion while maintaining recognition speed.
4Loss of information
If the server transmits a complete picture feature sample library to the AR device, then data completeness is improved, but transmission data volume increases
Solution Approach 1:
The server transmits only the locally relevant picture feature sub-library based on the AR device's geographic location, reducing transmission data volume while maintaining data completeness for the user's specific environment and needs.
Solution Approach 2:
The server extracts and transmits only the relevant geographic sub-library from the complete picture feature library, reducing transmission data volume while ensuring that all necessary picture features for the user's location are included.
Data Source
AI summary
A method includes: receiving, at a server and from an augmented reality device, user information of a user using the augmented reality device; generating, by the server, a picture feature sample sub-library corresponding to the user information, including screening out, from a preset picture feature sample library, picture feature samples associated with the user information; and providing, to the augmented reality device, the picture feature sample sub-library, wherein the picture feature sample sub-library can be configured to be used by the augmented reality device to perform, during image scanning of an offline environment of the user, image recognition of images scanned from the offline environment by comparing the scanned images to picture features in the picture feature sample sub-library.