Short-Side Excursion for Oriented Object Detection
Yuhu Cheng, Chengqing Xu, Yi Kong, Xuesong Wang · IEEE Geoscience and Remote Sensing Letters · 2022
Oriented object detection has achieved a significant progress in image processing. Compared with horizontal detection methods, oriented detectors add the orientation parameter in regression to locate objects. However, existing rotation and quadrilateral representations are not appropriate for oriented two-stage methods to generate efficient oriented proposals. In this paper, we propose a novel framework to detect oriented objects, termedshort side excursion detection(SSEDet). Inspired by the circle theorem, we propose a transformation method from horizontal rectangles to oriented ones to accurately describe oriented objects. To be specific, we exploit the offset of short sides relative to the top-right vertex to represent the orientation of rectangle. Compared with the horizontal rectangle, the representation parameters of oriented rectangle have only one more orientation parameter. Under the action of the orientation parameter, the one-to-one correspondence between representation parameters and oriented rectangle can be realized. Experimental results on commonly used datasets verify that SSEDet can generate high-quality oriented proposals.