Depth Imaging System Using ToF SPAD Range Detection
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Solution Overview
Problem
Current 3D/depth mapping technologies in devices like mobile phones face limitations in accuracy, speed, and power consumption due to multiple camera implementations, which are affected by noise, subject movement, device motion, and manufacturing inconsistencies, especially in low light conditions and mobile devices with limited computation power.
Innovation Solution
Integration of a Time of Flight (ToF) module with Single-photon avalanche diodes (SPADs) to determine distance, combined with camera modules, allowing the processor to adapt operation modes based on light intensity, speed, accuracy, range, and power usage to generate depth maps, improving accuracy, speed, and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple camera modules are used for depth mapping, then 3D imaging capability is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent combines multiple camera modules (first and second camera modules) with different optical characteristics into a unified depth mapping system. The processor integrates images from both cameras, leveraging their complementary fields of view and optical properties to achieve accurate depth mapping while managing system complexity through coordinated operation.
Solution Approach 2:
The camera system is designed to perform multiple functions: the first camera module captures wide-angle images for overall scene understanding, while the second camera module captures telephoto images for detailed depth information. This multi-functionality allows the system to adapt to different imaging scenarios and maintain accuracy across various depths.
2Productivity
If multiple camera modules operate simultaneously, then depth mapping speed is improved, but power consumption increases
Solution Approach 1:
The processor dynamically selects and switches between different camera modules based on real-time imaging requirements. When fast depth mapping is needed, both cameras can operate simultaneously. When power saving is prioritized, the processor can use only one camera module, adapting the system's operational state to current needs.
Solution Approach 2:
The system employs periodic switching between different camera configurations and operating modes. The processor alternates between using single camera modes for power saving and dual camera modes for high-speed depth mapping, creating a rhythmic pattern of operation that balances performance and energy consumption over time.
3Measurement precision
If computational algorithms are enhanced to correct errors, then depth mapping accuracy is improved, but computation power requirements increase
Solution Approach 1:
The system performs preliminary error correction and calibration during the manufacturing process. Intrinsic parameters and extrinsic parameters are pre-calculated and stored, so that during operation, the processor only needs to apply these pre-computed corrections rather than performing complex real-time calculations, significantly reducing computational power requirements.
Solution Approach 2:
The processor continuously refines depth mapping results by comparing images from both camera modules and applying iterative correction algorithms. The system uses feedback from the captured images to adjust and improve depth accuracy, progressively reducing errors while managing computational load through adaptive processing.
4Illumination intensity
If camera modules are used in low light conditions, then image capture is possible, but noise and accuracy deteriorate
Solution Approach 1:
The system changes operational parameters when operating in low light conditions. The processor adjusts exposure times, gain settings, and processing algorithms based on ambient light levels. By dynamically modifying these parameters, the system maintains depth mapping functionality in varying light conditions while compensating for increased noise through adaptive processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The ToF module enhances accuracy and speed while reducing variations and power consumption, enabling more reliable 3D/depth mapping across various conditions, including low light, and allowing for more efficient use in mobile devices by leveraging the strengths of both ToF and camera data.
Implementation Method 1
at least one ToF SPAD based range detecting module configured to generate at least one distance determination between the apparatus and an object
Implementation Method 2
ToF SPAD based range detecting module
Data Source
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AI summary
An apparatus (101) comprising: at least one camera module (111, 115) configured to generate at least one image; at least one ToF SPAD (113) based range detecting module configured to generate at least one distance determination between the apparatus (101) and an object (103) within a module field of view; and a processor (119) configured to receive at least one image from the at least one camera module output and at least one distance determination from the ToF SPAD based range detecting module output and based on the at least one camera module output and at least one distance determination to determine a depth map.