研究目的
To introduce a skeleton-based approach for fast, accurate, and continuous extrinsic calibration of multiple RGB-D Kinect cameras without manual intervention or external reference objects.
研究成果
The skeleton-based calibration method provides a fast, accurate, and non-invasive solution for extrinsic calibration of multiple Kinect cameras, enabling automatic re-calibration in real-time with minimal error.
研究不足
1. Dependency on Kinect for skeleton extraction limits the method to cameras providing skeleton data.
2. Depth estimation issues with glossy surfaces and interference between multiple Kinect sensors.
3. Limited depth capture range of Kinect V2 (0.5-3m) may not suffice for all applications.
1:Experimental Design and Method Selection:
The method uses skeletal joint correspondence from Kinect's skeleton tracking for calibration, applying temporal, spatial, and motion constraints for point selection.
2:Sample Selection and Data Sources:
The person's skeleton in the scene is used as the reference object, with joints selected based on visibility and tracking accuracy.
3:List of Experimental Equipment and Materials:
7 Kinect V2 sensors connected to individual computers, synchronized using Network Time Protocol (NTP).
4:Experimental Procedures and Operational Workflow:
Skeletal joints are extracted and used for pairwise camera calibration. Automatic re-calibration is performed based on continuous error checking.
5:Data Analysis Methods:
Calibration error is calculated by the maximum Euclidean distance between calibrated skeleton joints from different cameras.
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