{"title":"基于计算机视觉的行人和车道检测","authors":"R. Srija, K. Kumar","doi":"10.29027/ijirase.v3.i11.2019.416-419","DOIUrl":null,"url":null,"abstract":": The road network of India is over 52,31,922 kms. During 2015 , the total number of traffic accidents were 4,96,762 with 4,86,567 persons were injured and 1,77,423 were killed.In order to avoid such road accidents, the collision of pedestrian with the vehicle on the highway should be prevented. So an approach for automatic lane and pedestrian detection on highways to prevent road accidents using deep learning and computer vision techniques is proposed. The pedestrian detection is done using tensorflow and HOG detector. Lane detection ensures that the vehicles are within the lane constraints and avoids the collision with vehicles on the nearby lanes.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pedestrian and Lane Detection using Computer Vision\",\"authors\":\"R. Srija, K. Kumar\",\"doi\":\"10.29027/ijirase.v3.i11.2019.416-419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": The road network of India is over 52,31,922 kms. During 2015 , the total number of traffic accidents were 4,96,762 with 4,86,567 persons were injured and 1,77,423 were killed.In order to avoid such road accidents, the collision of pedestrian with the vehicle on the highway should be prevented. So an approach for automatic lane and pedestrian detection on highways to prevent road accidents using deep learning and computer vision techniques is proposed. The pedestrian detection is done using tensorflow and HOG detector. Lane detection ensures that the vehicles are within the lane constraints and avoids the collision with vehicles on the nearby lanes.\",\"PeriodicalId\":447225,\"journal\":{\"name\":\"International Journal of Innovative Research in Applied Sciences and Engineering\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovative Research in Applied Sciences and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29027/ijirase.v3.i11.2019.416-419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Research in Applied Sciences and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29027/ijirase.v3.i11.2019.416-419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pedestrian and Lane Detection using Computer Vision
: The road network of India is over 52,31,922 kms. During 2015 , the total number of traffic accidents were 4,96,762 with 4,86,567 persons were injured and 1,77,423 were killed.In order to avoid such road accidents, the collision of pedestrian with the vehicle on the highway should be prevented. So an approach for automatic lane and pedestrian detection on highways to prevent road accidents using deep learning and computer vision techniques is proposed. The pedestrian detection is done using tensorflow and HOG detector. Lane detection ensures that the vehicles are within the lane constraints and avoids the collision with vehicles on the nearby lanes.
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