{"title":"观察道路上的车辆行为:问题、方法和观点","authors":"Sayanan Sivaraman, B. Morris, M. Trivedi","doi":"10.1109/ITSC.2013.6728485","DOIUrl":null,"url":null,"abstract":"In this work, we review recent works comprising an emerging field of intelligent transportation: behavior analysis of vehicles. The ITS community has approached this topic both from vehicle-based and infrastructure-based sensing. In both cases, motion is the key indicator required for behavioral characterization, with accurate long-term prediction being the ultimate goal. However, the popular methods for behavior characterization differ between the sensing methodologies. Vehicle-based sensing tends to focus on spatio-temporal measurements coupled with various features for accurate estimation of object state. In contrast, infrastructure-sensing tends to avoid attempting high resolution estimation of vehicle state and prefers to utilize patterns learned in aggregate for constrained estimation. This review focuses on vision-based sensing and provides highlights of state-of-the art methods used in surveillance, and on-road vision modalities. We provide discussion and comment on future directions in the field.","PeriodicalId":275768,"journal":{"name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Observing on-road vehicle behavior: Issues, approaches, and perspectives\",\"authors\":\"Sayanan Sivaraman, B. Morris, M. Trivedi\",\"doi\":\"10.1109/ITSC.2013.6728485\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we review recent works comprising an emerging field of intelligent transportation: behavior analysis of vehicles. The ITS community has approached this topic both from vehicle-based and infrastructure-based sensing. In both cases, motion is the key indicator required for behavioral characterization, with accurate long-term prediction being the ultimate goal. However, the popular methods for behavior characterization differ between the sensing methodologies. Vehicle-based sensing tends to focus on spatio-temporal measurements coupled with various features for accurate estimation of object state. In contrast, infrastructure-sensing tends to avoid attempting high resolution estimation of vehicle state and prefers to utilize patterns learned in aggregate for constrained estimation. This review focuses on vision-based sensing and provides highlights of state-of-the art methods used in surveillance, and on-road vision modalities. We provide discussion and comment on future directions in the field.\",\"PeriodicalId\":275768,\"journal\":{\"name\":\"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2013.6728485\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2013.6728485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Observing on-road vehicle behavior: Issues, approaches, and perspectives
In this work, we review recent works comprising an emerging field of intelligent transportation: behavior analysis of vehicles. The ITS community has approached this topic both from vehicle-based and infrastructure-based sensing. In both cases, motion is the key indicator required for behavioral characterization, with accurate long-term prediction being the ultimate goal. However, the popular methods for behavior characterization differ between the sensing methodologies. Vehicle-based sensing tends to focus on spatio-temporal measurements coupled with various features for accurate estimation of object state. In contrast, infrastructure-sensing tends to avoid attempting high resolution estimation of vehicle state and prefers to utilize patterns learned in aggregate for constrained estimation. This review focuses on vision-based sensing and provides highlights of state-of-the art methods used in surveillance, and on-road vision modalities. We provide discussion and comment on future directions in the field.