{"title":"用于提高车辆实时态势感知的自动拼接","authors":"David Nam, N. Aouf","doi":"10.1109/IVS.2017.7995867","DOIUrl":null,"url":null,"abstract":"Situational awareness is increasingly important across many applications. Having a more adept sense of situational awareness leads to better understanding and prediction in various scenarios. This is apparent with the increasing use of infrared cameras. The benefits of infrared imaging make it an attractive option for use in ground vehicles. However, they are limited in their field-of-views. We propose an automated mosaicing method, to improve situational awareness, using infrared images from a vehicle mounted camera. Within our method we also propose a novel key frame selection algorithm, for efficient real time mosaicing. We validate our algorithm using different driving speeds, showing that it is robust across different driving scenarios.","PeriodicalId":143367,"journal":{"name":"2017 IEEE Intelligent Vehicles Symposium (IV)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automated mosaicing for improving vehicle situational awareness in real time\",\"authors\":\"David Nam, N. Aouf\",\"doi\":\"10.1109/IVS.2017.7995867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Situational awareness is increasingly important across many applications. Having a more adept sense of situational awareness leads to better understanding and prediction in various scenarios. This is apparent with the increasing use of infrared cameras. The benefits of infrared imaging make it an attractive option for use in ground vehicles. However, they are limited in their field-of-views. We propose an automated mosaicing method, to improve situational awareness, using infrared images from a vehicle mounted camera. Within our method we also propose a novel key frame selection algorithm, for efficient real time mosaicing. We validate our algorithm using different driving speeds, showing that it is robust across different driving scenarios.\",\"PeriodicalId\":143367,\"journal\":{\"name\":\"2017 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2017.7995867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2017.7995867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated mosaicing for improving vehicle situational awareness in real time
Situational awareness is increasingly important across many applications. Having a more adept sense of situational awareness leads to better understanding and prediction in various scenarios. This is apparent with the increasing use of infrared cameras. The benefits of infrared imaging make it an attractive option for use in ground vehicles. However, they are limited in their field-of-views. We propose an automated mosaicing method, to improve situational awareness, using infrared images from a vehicle mounted camera. Within our method we also propose a novel key frame selection algorithm, for efficient real time mosaicing. We validate our algorithm using different driving speeds, showing that it is robust across different driving scenarios.