公开(公告)号：US20220148292A1

公开(公告)日：2022-05-12

申请号：US17257704

申请日：2020-03-13

Applicant: DALIAN UNIVERSITY OF TECHNOLOGY

Inventor： Xin YANG ,  Xiaopeng WEI ,  Qiang ZHANG ,  Haiyang MEI ,  Yuanyuan LIU

IPC: G06V10/774 ,  G06V10/77 ,  G06V10/80 ,  G06V10/70 ,  G06V10/776 ,  G06V10/44

Abstract: The invention discloses a method for glass detection in a real scene, which belongs to the field of object detection. The present invention designs a combination method based on LCFI blocks to effectively integrate context features of different scales. Finally, multiple LCFI combination blocks are embedded into the glass detection network GDNet to obtain large-scale context features of different levels, thereby realize reliable and accurate glass detection in various scenarios. The glass detection network GDNet in the present invention can effectively predict the true area of glass in different scenes through this method of fusing context features of different scales, successfully detect glass with different sizes, and effectively handle with glass in different scenes. GDNet has strong adaptability to the various glass area sizes of the images in the glass detection dataset, and has the highest accuracy in the field of the same type of object detection.