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12 June 2020 Target localization based on arbitrary angle bounding box for remote sensing image
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Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 115190Z (2020) https://doi.org/10.1117/12.2573136
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan
Abstract
State-of-the-art object detection networks have reduced the running time and get better detection results. However, for remote sensing image scenes, in a certain projection direction, the remote sensing image target will be tilted, The positioning of the horizontal bounding box used by the exit detection algorithm will cause a lot of overlap between the target bounding boxes, After using NMS (Non-maximum suppression),it will lead to the lost of the target. In this paper,we propose a Rotated Faster R-CNN(R-FRCNN) that is a target positioning method based on arbitrary angle bounding box,which can perform non-redundant positioning on the target,thus can reduce the missed detection rate. when the target is densely distributed or the angle of the object is arbitrary.Compared with traditional and state-ofthe art object detection algorithms,our approach obtain the superior performance.
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Yinhua Li, Shouhong Wan, Peiquan Jin, and XingYue Li "Target localization based on arbitrary angle bounding box for remote sensing image", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 115190Z (12 June 2020); https://doi.org/10.1117/12.2573136
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