Rail transit scene 3D target detection method based on image and point cloud feature fusion and storage medium

By adopting the detection method of image and point cloud features fusion in rail transit scenes, using the bidirectional cascade feature fusion and consistency loss function, the problems of poor target detection effect and insufficient multi-sensor fusion feature extraction in the existing technology are solved, and high-precision 3D object detection is achieved to meet the needs of all-weather rail transit scenes.

CN119919763APending Publication Date: 2025-05-02ZHUZHOU CSR TIMES ELECTRIC CO LTD
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Patent Information

Application Number
CN202311414570.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2023-10-30
Publication Date
2025-05-02

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Abstract

The invention discloses a rail transit scene 3D target detection method based on image and point cloud feature fusion and a storage medium. The method comprises the steps of S1, performing dual-channel multi-scale feature extraction on acquired vehicle-mounted camera image data and laser radar point cloud data; s2, deep fusion is carried out on the features of different scales in a bidirectional cascade feature fusion mode, and enhanced fusion features containing image semantic information and point cloud geometric information are obtained; s3, carrying out point-by-point classification and prediction frame extraction on the enhanced fusion features obtained in the step S2; and S4, obtaining a final 3D detection result through screening. A computer program for executing the method is stored in the storage medium. The method has the advantages of being simple in principle, wide in application range, capable of greatly improving the detection precision and the like.
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