Depth Map Registration for Multi-Sensor Depth Accuracy
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Solution Overview
Problem
Single depth sensors have limitations in capturing a wide range of object depths, especially in regions with repeated textures or high light absorption, leading to errors in depth value determination and accuracy verification.
Innovation Solution
A depth data processing system comprising a first depth capture device, a second depth capture device, and a depth processing unit that generates and aligns depth maps using image registration to produce an optimized depth map, leveraging transformed coordinates to complement and correct depth data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single depth sensor is used to capture depth data, then the device complexity is reduced, but the measurement precision and reliability of depth values deteriorate in regions with repeated textures or high light absorption
Solution Approach 1:
The patent combines data from multiple depth sensors (first depth map and second depth map) to create a fused depth map. By merging the depth information from different sensors with different baselines, the system achieves more accurate depth measurement in challenging regions where single sensors fail, resolving the contradiction between device simplicity and measurement precision.
Solution Approach 2:
The patent introduces image registration as an intermediary process that transforms coordinates between different depth maps. This intermediary step enables accurate alignment and fusion of depth data from multiple sensors, allowing the system to verify and correct depth values by comparing them across different sensor perspectives.
2Device complexity
If a single depth sensor is used, then the hardware requirements are simplified, but the ability to verify accuracy of depth values is lost
Solution Approach 1:
The system merges depth maps from multiple sensors to create a fused depth map, enabling cross-verification of depth values. By combining data from the first and second depth sensors, the system can identify and correct erroneous depth measurements, thereby improving reliability without requiring overly complex hardware.
Solution Approach 2:
The patent implements a feedback mechanism where the fused depth map is used to verify and correct the original depth maps. The image registration process provides feedback by comparing transformed coordinates across different sensors, allowing the system to identify and correct inaccurate depth values, thus enhancing reliability.
3Measurement precision
If multiple depth sensors are used to improve depth data accuracy, then the measurement precision improves, but the device complexity and processing requirements increase
Solution Approach 1:
The patent segments the depth capture function into multiple specialized sensors with different configurations (different baselines). Each sensor captures depth data from its specific perspective, and the segmentation allows the system to process and fuse these specialized data streams to achieve superior measurement precision while managing complexity through functional division.
Solution Approach 2:
The patent adds the dimension of multiple sensor perspectives by using depth sensors with different baselines. This dimensional approach allows the system to capture depth information from multiple viewpoints, enabling accurate verification and fusion of depth data to improve measurement precision while distributing the processing load across different sensor configurations.
4Reliability
If image registration is performed on depth maps from multiple sensors, then the reliability of depth data improves, but the processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary actions by establishing transformation models and coordinate systems for each depth sensor before actual depth capture. By pre-configuring the registration parameters and transformation relationships, the system reduces the computational burden during real-time processing, thereby improving reliability through thorough verification while minimizing processing time loss.
Data Source
AI summary
An operating method includes generating a first depth map by at least a first depth capture device, generating a second depth map by at least a second depth capture device, performing image registration on the first depth map with the second depth map to obtain transformed coordinates in the second depth map corresponding to pixels in the first depth map, and aligning depth data of the first depth map and depth data of the second depth map to generate an optimized depth map according to the transformed coordinates in the second depth map corresponding to the pixels in the first depth map.