Environment Recognition for Depth Estimation Beyond Stereo Overlap
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Solution Overview
Problem
Existing depth estimation techniques using stereo cameras face accuracy issues in regions where fields of view do not overlap, as they rely on direct distance measurement from overlapping regions, leading to degraded estimation accuracy.
Innovation Solution
An environment recognition apparatus and method that utilizes a first depth computation unit for overlapping regions and a second depth computation unit for non-overlapping regions, employing relevance ratio computation and feature integration to estimate depth accurately in non-overlapping regions using two-dimensional and three-dimensional information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a distance in a field of view overlapped region is directly taken as a distance to an object, then the depth estimation in the overlapped region is simplified, but the estimation accuracy is degraded when the distance measurement is wrong
Solution Approach 1:
The patent introduces an intermediary process between direct distance measurement and final depth estimation. A relevance ratio computation unit calculates the reliability of depth information from the overlapped region, and this relevance ratio is used to weight and correct the depth estimation in the non-overlapped region, rather than directly adopting the overlapped region depth value.
Solution Approach 2:
The patent implements a feedback mechanism where the depth computation unit uses the relevance ratio (which reflects the quality of depth measurement) to adjust and correct the depth estimation. The system continuously evaluates measurement quality and uses this feedback to improve estimation accuracy in regions where direct measurement is unreliable.
2Device complexity
If depth measurement is performed only in the field of view overlapped region, then the measurement process is simple, but it cannot be applied to objects in the field of view non-overlapped region
Solution Approach 1:
The patent divides the image space into three distinct regions: first overlapped region, second non-overlapped region, and third region. Different depth computation strategies are applied to each region, allowing the system to handle objects in all regions while maintaining measurement accuracy through region-specific processing.
Solution Approach 2:
The patent extends depth estimation from the two-dimensional overlapped region into the third spatial dimension by projecting depth information to adjacent non-overlapped regions. This dimensional extension allows depth estimation for objects that are not directly visible in the overlapped region, significantly improving system versatility.
3Ease of operation
If depth estimation in non-overlapping regions is performed using direct distance measurement from overlapping regions, then the process is straightforward, but accuracy is degraded due to error propagation
Solution Approach 1:
The patent changes the parameter used for depth estimation by introducing a relevance ratio that quantifies the reliability of depth information. Instead of directly using distance measurements, the system computes a relevance ratio based on measurement quality, and uses this parameter to weight and correct depth estimates, thereby improving accuracy while maintaining operational simplicity.
Data Source
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AI summary
Provided are an environment recognition device and an environment recognition method which are capable of achieving a highly accurate depth estimation in a field of view non-overlap region. This environment recognition device is characterized by comprising: an image acquisition unit for acquiring an image captured by a camera; a first depth calculation unit which calculates a first depth in a first region which partially overlaps or is adjacent to the field of view of the camera; and a second depth calculation unit which uses the first depth in the first region and the image captured by the camera and calculates a second depth in a second region which is not included in the first region in the field of view of the camera.