G. Shanmugasundaram, Dr. C. PunithaDevi, S. Balaji, T. Mugilan
{"title":"STATIC OBSTACLE DETECTION FOR SECURITY IN SURVEILLANCE","authors":"G. Shanmugasundaram, Dr. C. PunithaDevi, S. Balaji, T. Mugilan","doi":"10.1109/ICSCAN.2018.8541221","DOIUrl":null,"url":null,"abstract":"In recent times, we hear a lot of unexpected incidents happening in crowded places carried out by explosives hidden inside abandoned baggage or left behind items especially in India like country. Even though security cameras are placed, which monitors and raise alarms at the right time is still a manual activity that leads to mistakes and delayed detection. With the advancement in surveillance camera electronics and image processing algorithms such as Haar cascade classifier algorithm, Support Vector Machine (SVM), etc., and images can be detected using Deep learning object detection ,Feature- based object detection where it is possible to automate such detection. The objective of this article is to explore a various factors and its importance in object detection. Further it also explores about the existing techniques and models used in detection of objects. This article concludes with various challenges in object detection which are not yetaddressed.","PeriodicalId":378798,"journal":{"name":"2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCAN.2018.8541221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In recent times, we hear a lot of unexpected incidents happening in crowded places carried out by explosives hidden inside abandoned baggage or left behind items especially in India like country. Even though security cameras are placed, which monitors and raise alarms at the right time is still a manual activity that leads to mistakes and delayed detection. With the advancement in surveillance camera electronics and image processing algorithms such as Haar cascade classifier algorithm, Support Vector Machine (SVM), etc., and images can be detected using Deep learning object detection ,Feature- based object detection where it is possible to automate such detection. The objective of this article is to explore a various factors and its importance in object detection. Further it also explores about the existing techniques and models used in detection of objects. This article concludes with various challenges in object detection which are not yetaddressed.