Monocular Depth Reliability Using Ground Region Segmentation
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Solution Overview
Problem
Monocular depth estimation techniques suffer from accuracy deterioration when the ground portion between a subject and the ground is unclear, leading to potential inaccuracies in depth estimation, especially in applications like automated driving where precise depth information is crucial.
Innovation Solution
An image processing apparatus that includes a depth information acquisition unit, a ground region determination unit, and a reliability calculation unit to determine the ground region and assign reliability to the acquired depth, enhancing the accuracy of depth estimation by segmenting the image and assigning high reliability to regions in contact with the ground.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If monocular depth estimation is used to acquire depth information, then depth information can be obtained using simple hardware, but accuracy deteriorates when ground portion between subject and ground is unclear
Solution Approach 1:
The image is segmented into ground regions and non-ground regions using image segmentation technology. By dividing the image into distinct segments, the system can identify which portions correspond to ground contact areas, thereby improving depth estimation accuracy in regions where ground portion is unclear while maintaining the use of simple monocular camera hardware.
Solution Approach 2:
Different reliability values are assigned to different regions of the image based on whether they are ground regions or non-ground regions. Ground regions are assigned higher reliability while non-ground regions receive lower reliability. This local differentiation allows the system to maintain high accuracy where ground contact is visible while still providing depth information elsewhere, resolving the accuracy issue without complicating the hardware.
2Productivity
If monocular depth estimation is used in automated driving, then depth information of densely located objects can be acquired, but inaccurate depth values may occur due to occlusion
Solution Approach 1:
The system performs preliminary identification of ground regions before final depth estimation. By first determining which regions are ground regions using image segmentation, the system can then apply appropriate reliability weighting to depth values. This preliminary action ensures that depth information from occluded or uncertain regions is properly flagged, maintaining both comprehensive coverage and accuracy in automated driving applications.
Solution Approach 2:
The reliability calculation unit provides feedback about the quality of depth information by assigning reliability values based on ground region determination. This feedback mechanism allows downstream processing to understand which depth values are trustworthy and which may be inaccurate due to occlusion, enabling better decision-making in path planning and obstacle avoidance while maintaining comprehensive depth coverage.
3Measurement precision
If ground region determination and reliability calculation are added to depth estimation system, then depth estimation reliability is improved, but device complexity increases
Solution Approach 1:
The system uses multi-functional processing units that perform multiple tasks. The image segmentation technology serves both to identify ground regions and to provide structural information for depth estimation. The reliability calculation unit integrates with the existing depth estimation pipeline, adding reliability assessment without requiring completely separate processing chains. This multi-functionality improves depth reliability while minimizing the increase in device complexity.
Solution Approach 2:
The ground region determination acts as an intermediary between the monocular depth estimation and the final depth output. Rather than directly modifying the depth estimation algorithm, the system introduces a ground region identification layer that mediates between the simple monocular input and the reliability-weighted output, improving precision while keeping the overall system architecture relatively simple.
Data Source
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AI summary
An image processing apparatus (100) that obtains a depth from an input image includes: a depth information acquisition unit (101) configured to acquire depth information; a ground region determination unit (102) configured to determine a ground region of a subject of the image; and a reliability calculation unit (103) configured to calculate reliability for the depth acquired by the depth information acquisition unit based on the determination of the ground region determination unit. Here, the depth is an absolute distance between a standard point and a subject or an evaluation value relatively indicating a distance between a standard point and a subject. The reliability calculation unit calculates high reliability for a depth of a pixel of the ground region or a segmented region including the ground region.