The vehicles and pedestrians ranging is one of the basic functions of advanced driving assistance system.However,most of the ranging systems can only work on workstations with high computing power.To solve this proble...The vehicles and pedestrians ranging is one of the basic functions of advanced driving assistance system.However,most of the ranging systems can only work on workstations with high computing power.To solve this problem,a lightweight algorithm is proposed to be packaged into Android application package,and be installed in Android smartphones for vehicles and pedestrians ranging.The proposed ranging system is based on the images obtained by smartphone’s monocular camera.To achieve real-time ranging,an 8-bit integer(int8)quantization algorithm is proposed to accelerate the inference of convolutional neural networks.To increase the detection precision,a zoom-in algorithm is further proposed to detect small targets in the distance.After having detected the 2D bounding boxes of vehicles and pedestrians,a pinhole ranging method is applied to estimate the distance.In order to verify the proposed algorithm,the mean average precision(mAP)and the frame per second(FPS)are first tested by using COCO dataset on Huawei P40Pro,then,the ranging precision on the real road.The experimental results show that this algorithm can successfully perform real-time ranging(15 FPS)with high precision(34.8 mAP)onto the tested smartphones.Finally,a possible mobile application based on the ranging algorithm,i.e.,distance keeping warning,is also provided.展开更多
基金the RoboCar Project for Internationalization of RTI Projects within the Frame of the Austrian Research Promotion Agency(No.861000)。
文摘The vehicles and pedestrians ranging is one of the basic functions of advanced driving assistance system.However,most of the ranging systems can only work on workstations with high computing power.To solve this problem,a lightweight algorithm is proposed to be packaged into Android application package,and be installed in Android smartphones for vehicles and pedestrians ranging.The proposed ranging system is based on the images obtained by smartphone’s monocular camera.To achieve real-time ranging,an 8-bit integer(int8)quantization algorithm is proposed to accelerate the inference of convolutional neural networks.To increase the detection precision,a zoom-in algorithm is further proposed to detect small targets in the distance.After having detected the 2D bounding boxes of vehicles and pedestrians,a pinhole ranging method is applied to estimate the distance.In order to verify the proposed algorithm,the mean average precision(mAP)and the frame per second(FPS)are first tested by using COCO dataset on Huawei P40Pro,then,the ranging precision on the real road.The experimental results show that this algorithm can successfully perform real-time ranging(15 FPS)with high precision(34.8 mAP)onto the tested smartphones.Finally,a possible mobile application based on the ranging algorithm,i.e.,distance keeping warning,is also provided.
