{"title":"预处理更快的RCNN车辆检测","authors":"Mduduzi Manana, Chunling Tu, P. Owolawi","doi":"10.1109/ICONIC.2018.8601243","DOIUrl":null,"url":null,"abstract":"This paper presents a pre-processed faster region convolution neural network (faster RCNN) for the purpose of on-road vehicle detection. The system introduces a preprocessing pipeline on faster RCNN. The preprocessing method is for the improvement on training and detection speed of Faster RCNN. A preprocessing lane detection pipeline based on the Sobel edge operator and Hough Transform is used to detect lanes. A Rectangular region is then extracted from lane coordinates which is a reduced region of interest (ROI). Results show that the proposed method improves the training speed of faster RCNN when compared to faster RCNN without preprocessing.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Preprocessed Faster RCNN for Vehicle Detection\",\"authors\":\"Mduduzi Manana, Chunling Tu, P. Owolawi\",\"doi\":\"10.1109/ICONIC.2018.8601243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a pre-processed faster region convolution neural network (faster RCNN) for the purpose of on-road vehicle detection. The system introduces a preprocessing pipeline on faster RCNN. The preprocessing method is for the improvement on training and detection speed of Faster RCNN. A preprocessing lane detection pipeline based on the Sobel edge operator and Hough Transform is used to detect lanes. A Rectangular region is then extracted from lane coordinates which is a reduced region of interest (ROI). Results show that the proposed method improves the training speed of faster RCNN when compared to faster RCNN without preprocessing.\",\"PeriodicalId\":277315,\"journal\":{\"name\":\"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONIC.2018.8601243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONIC.2018.8601243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a pre-processed faster region convolution neural network (faster RCNN) for the purpose of on-road vehicle detection. The system introduces a preprocessing pipeline on faster RCNN. The preprocessing method is for the improvement on training and detection speed of Faster RCNN. A preprocessing lane detection pipeline based on the Sobel edge operator and Hough Transform is used to detect lanes. A Rectangular region is then extracted from lane coordinates which is a reduced region of interest (ROI). Results show that the proposed method improves the training speed of faster RCNN when compared to faster RCNN without preprocessing.