Depth Imaging System Deformation Detection and Automatic Calibration
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Solution Overview
Problem
Depth imaging systems, such as those used in head-mounted displays, face inaccuracies in depth information due to physical deformations caused by environmental changes, handling, or assembly strain, which alter the extrinsic calibration of the projector and camera, leading to misalignment and incorrect depth mapping.
Innovation Solution
A method and apparatus that detect deformation in the depth imaging system by analyzing the relationship between projected and reflected pattern features, allowing for automatic recalibration of extrinsic calibration parameters to maintain accurate depth mapping, even in the presence of small physical deformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the depth imaging system uses original extrinsic calibration information, then the system structure remains simple, but the depth information becomes inaccurate after physical deformation
Solution Approach 1:
The system performs self-calibration by automatically detecting deformation through feature point analysis and updating its own extrinsic calibration parameters without external intervention. The processor compares projected pattern features with captured image features to detect misalignment and recalibrates the system autonomously.
Solution Approach 2:
The system establishes a feedback loop where depth information accuracy is continuously monitored by analyzing the relationship between projected and captured pattern features. When deformation is detected through feature point misalignment, the system automatically adjusts extrinsic calibration parameters to maintain accuracy.
2Measurement precision
If the system performs automatic recalibration after deformation, then depth information accuracy is maintained, but the operation time and processing complexity increase
Solution Approach 1:
The system performs preliminary deformation detection by continuously analyzing the relationship between projected pattern features and captured image features. When misalignment is detected, recalibration is triggered immediately, preventing prolonged periods of inaccurate depth measurement.
Solution Approach 2:
The system dynamically adjusts extrinsic calibration parameters based on detected deformation. By changing these parameters in response to environmental conditions (temperature, handling), the system maintains measurement accuracy without requiring complete recalibration procedures.
3Measurement precision
If the system requires dedicated calibration hardware and user intervention, then calibration accuracy can be ensured, but the ease of operation and user convenience decrease
Solution Approach 1:
The system eliminates the need for external calibration hardware and user intervention by performing self-calibration using its own projected pattern and captured images. The processor automatically detects deformation through feature point analysis and updates calibration parameters without user involvement.
Solution Approach 2:
The system uses the existing projector and camera for both depth measurement and calibration purposes. The projected pattern serves dual functions: as the illumination pattern for depth sensing and as the reference pattern for detecting deformation and performing recalibration.
Data Source
AI summary
Disclosed are an apparatus and a method for detecting deformation of a structured light depth imaging system and automatic re-calibration for the depth imaging system. In one embodiment, a depth imaging device includes a light projector, a camera and a processor. The light projector emits light corresponding to a projected pattern image having a plurality of features with known locations in the projected pattern image. The camera captures the light reflected by an environment of the depth imaging device and generates a reflected pattern image as a two-dimensional (2D) projection of the environment. The reflected pattern image includes a plurality of features that correspond to the features of the projected pattern image. The processor detects a misalignment for a distance or an orientation between the light projector and the camera based on a relationship between the features in the projected pattern image and the features in the reflected pattern image.