Single-Sensor Depth Extraction via Computational Blur Segmentation
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Solution Overview
Problem
Existing depth perception technologies, such as stereoscopic and motion parallax methods, are computationally intensive and require complex hardware configurations, while depth-from-defocus systems face accuracy issues and are prone to hardware drawbacks like multiple sensor alignment problems.
Innovation Solution
A single-lens, single-sensor system captures images at varying degrees of focus without moving parts, using a computer processor to determine depth by comparing blur differences, allowing for compact, robust 3D imaging with reduced processing requirements and simplified feature matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used for depth-from-defocus imaging, then depth measurement capability is improved, but hardware complexity and alignment issues increase
Solution Approach 1:
The patent divides a single sensor into multiple virtual subarrays through computational processing. Each subarray processes light from different angular directions, enabling depth-from-defocus measurements without physical multiple sensors. This segmentation is achieved by assigning different pixels to different virtual subarrays and processing their signals separately to extract depth information.
Solution Approach 2:
The patent creates virtual copies of sensor functionality through computational methods. Instead of using multiple physical sensors, it simulates multiple sensor arrays by processing signals from a single sensor in different ways, assigning different pixels to different virtual subarrays that mimic the behavior of separate physical sensors.
2Measurement precision
If multiple sensors are used for depth-from-defocus imaging, then depth measurement capability is improved, but alignment precision requirements increase
Solution Approach 1:
The patent segments a single sensor into multiple virtual subarrays, eliminating the need for physical alignment between multiple sensors. Each virtual subarray is defined computationally by assigning specific pixels to different subarrays, requiring no physical alignment precision beyond standard single-sensor manufacturing tolerances.
3Measurement precision
If lens movement is used to acquire images with different blur quantities, then depth information acquisition is improved, but device complexity and dynamic issues increase
Solution Approach 1:
The patent uses a movable mirror to dynamically redirect light to different subarrays, creating different blur quantities without moving the lens. This dynamic element provides the necessary variation in blur while keeping the lens assembly stationary, avoiding the complexity of moving heavy lens components.
Solution Approach 2:
The patent replaces the mechanical lens movement system with a lighter, simpler movable mirror system. Instead of moving the entire lens assembly to change focus, a small mirror is moved to redirect light paths, achieving the same effect with minimal mechanical complexity and mass.
4Measurement precision
If stereoscopic vision is used for depth perception, then depth accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent extracts depth information directly from the blur quantity of each pixel without requiring complex correspondence matching between multiple images. By taking out and analyzing the blur characteristic of light arriving at different angles, the system achieves depth measurement with simpler computations compared to full stereoscopic processing.
Solution Approach 2:
The patent changes the optical parameter of blur quantity to encode depth information. By controlling and measuring the blur quantity of light arriving at different subarrays, the system transforms depth measurement into a parameter-based calculation rather than a complex image matching problem, improving computational efficiency.
5Measurement precision
If motion parallax is used for depth estimation, then depth perception capability is improved, but device complexity increases
Solution Approach 1:
The patent introduces a dynamic movable mirror that can be positioned at different angles to redirect light to different subarrays. This dynamic element enables the system to estimate depth through controlled light path variations without requiring physical movement of the entire camera or complex mechanical structures.
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
This approach provides accurate 3D measurements with minimal hardware complexity, enabling compact designs suitable for consumer cameras and machine vision applications, reducing alignment issues and operational complexity while maintaining high spatial resolution.
Implementation Method 1
an optical element is provided to vary a degree of blur of light from different depths
Implementation Method 2
a sensor is provided to detect the light
Data Source
AI summary
Hardware and software methodology are described for three-dimensional imaging in connection with a single sensor. A plurality of images is captured at different degrees of focus without focus change of an objective lens between such images. Depth information is extracted by comparing image blur between the images captured on the single sensor.