Multi-Camera Mobile Device for Augmented Reality Depth Detection
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Solution Overview
Problem
Current augmented-reality systems lack effective methods for users to interact and digitally manipulate their environment, particularly in real-time and across multiple devices, limiting the depth and range of user engagement and collaboration.
Innovation Solution
A mobile device equipped with an array of fixed-gradient focused digital cameras and image sensors, allowing for the detection of objects and user gestures, and enabling the overlay of augmented reality elements that can be manipulated by users, with features like image recognition and social network integration for shared experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single digital camera is used for augmented reality, then the device complexity is low, but the measurement precision of depth and object detection is insufficient
Solution Approach 1:
The system divides the imaging function into multiple specialized cameras, each with a specific focal length optimized for different depth ranges. This segmentation allows each camera to excel at capturing objects at its designated distance, thereby improving overall depth detection precision without requiring a single complex camera system.
Solution Approach 2:
The patent transitions from a single-camera 2D imaging approach to a multi-camera 3D imaging system. By adding the dimension of multiple cameras with varying focal lengths, the system achieves superior depth perception and spatial awareness, enabling more precise augmented reality object placement and interaction.
2Adaptability or versatility
If multiple fixed-focus image sensors with different focus ranges are used, then the depth of field coverage is improved, but the device complexity increases
Solution Approach 1:
Each image sensor in the array is designed with a specific fixed focus range, creating a universal system where different sensors handle different depth zones. This multi-functional approach allows the device to capture objects across various distances simultaneously, improving adaptability without requiring each sensor to be adjustable.
Solution Approach 2:
The system varies the focal length parameter across different image sensors to optimize depth of field coverage. By carefully selecting and arranging sensors with progressively different focal lengths, the system achieves comprehensive depth coverage while maintaining fixed-focus simplicity for each individual sensor.
3Speed
If real-time object detection and gesture recognition are implemented, then the user interaction responsiveness is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing by having multiple cameras continuously capture images in their respective depth zones, pre-identifying objects and gestures before user interaction occurs. This preliminary action reduces the processing time required during actual interaction, improving responsiveness without excessive computational burden during critical moments.
Solution Approach 2:
The multi-camera system maintains continuous image capture and processing across all depth zones simultaneously, ensuring that objects and gestures are always being monitored. This continuous useful action eliminates processing delays and maintains high responsiveness for real-time augmented reality interactions.
Data Source
AI summary
In one aspect, a method of a mobile-device control with a plurality of rear-facing fixed-focus image sensors including the step of providing a mobile device. The mobile device comprises an array comprising a plurality of rear-facing fixed-focus image sensors. Each fixed-focus image sensors comprises a different focus range value. The method includes the step of associating each rear-facing fixed-focus image sensors with a command input of the mobile device. The method includes the step of detecting a specified object in a depth of field of a specified rear-facing fixed-focus image sensor of the rear-facing fixed-focus image sensors. The method includes the step of implementing the command input of the mobile device associated with the specified rear-facing fixed-focus image sensor.