Scene reconstruction method, apparatus, storage medium, and electronic device
A camera-based scene reconstruction method addresses the high cost of laser radar by segmenting scenes and performing sparse and dense reconstructions, reducing costs and enhancing efficiency.
JP2026521130APending Publication Date: 2026-06-26BEIJING HORIZON INFORMATION TECH CO LTD
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Patent Information
- Application Number
- JP2025569551
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-06-30
- Filing Date
- 2024-06-26
- Publication Date
- 2026-06-26
AI Technical Summary
Technical Problem
Current scene reconstruction methods rely on expensive laser radar, leading to high implementation costs.
Method used
A method and apparatus that utilize a camera-mounted device for background segmentation, sparse and dense point cloud reconstruction, and dynamic/static scene segmentation to reduce costs and improve reconstruction efficiency.
Benefits of technology
The method reduces the cost of scene reconstruction by using a camera-based approach, allowing for separate processing of static and dynamic scenes, thereby lowering implementation costs and improving reconstruction speed and accuracy.
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Smart Images
Figure 2026521130000001_ABST
Abstract
The scene reconstruction method includes the steps of: obtaining a second image sequence by performing background segmentation on a first image sequence collected by a camera mounted on a movable device; obtaining a first reconstructed point cloud and a first camera position and orientation sequence by performing sparse reconstruction of the point cloud using the second image sequence; obtaining a third image sequence and a fourth image sequence by performing dynamic static segmentation on the first image sequence; obtaining a second reconstructed point cloud by performing dense reconstruction of the point cloud using the first reconstructed point cloud, the first camera position and orientation sequence and the third image sequence; obtaining a third reconstructed point cloud using the first camera position and orientation sequence and the fourth image sequence; and determining the scene reconstruction result based on the second and third reconstructed point clouds.
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