A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown mar...A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown maritime environment.The stimulation competition and selection mechanism in the visual pathway of raptor vision based on the phenomenon of raptor capturing prey in complex scenes are studied.Then,the mathematical model of the stimulation competition and selection mechanism of raptor vision is established and employed for the salient object detection.Popular image datasets and practical scene datasets are applied to verify the effectiveness of the presented method.Results show that the detection performance of the proposed method is better than that of other comparison methods.The proposed algorithm provides an idea for maritime target salient detection and cross-domain joint mission for UAV or other unmanned equipment.展开更多
基金supported by the National Natural Science Foundation of China under grant#62103040,#U1913602,#T2121003,#91948204,#U20B2071,and#U19B2033 and Open Fund/Postdoctoral Fund of the Laboratory of Cognition and Decision Intelligence for Complex Systems,Institute of Automation,Chinese Academy of Sciences under grant CASIA-KFKT-08.
文摘A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown maritime environment.The stimulation competition and selection mechanism in the visual pathway of raptor vision based on the phenomenon of raptor capturing prey in complex scenes are studied.Then,the mathematical model of the stimulation competition and selection mechanism of raptor vision is established and employed for the salient object detection.Popular image datasets and practical scene datasets are applied to verify the effectiveness of the presented method.Results show that the detection performance of the proposed method is better than that of other comparison methods.The proposed algorithm provides an idea for maritime target salient detection and cross-domain joint mission for UAV or other unmanned equipment.