Regression-based camera pose estimation through multi-level local features and global features

HIGHLIGHTS

• who: Sensors and collaborators from the School of Electronic Engineering and Computer Science, Queen Mary University of London have published the research work: Regression-Based Camera Pose Estimation through Multi-Level Local Features and Global Features, in the Journal: Sensors 2023, 4063 of /2023/
• what: The authors propose a novel relative camera pose regression framework that uses global features with rotation consistency and local features with rotation invariance. The authors propose a novel end-to-end camera pose estimation framework that uses image pairs as input and leverages epipolar geometry to generate image pixel pairs . . .
  

   

  

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