{"title":"一种新的人体头部快速检测算法","authors":"Yangming He, Shuguang Dai","doi":"10.1109/ICNDS.2009.110","DOIUrl":null,"url":null,"abstract":"According to the features of human head which is taken by camera shooting from the top down, this paper puts forward a new and rapid algorithm for detecting human head. First, the image is binarized by threshold, then searches diameter of circular-like head area in binary image. If the diameter is in conformity with the feature of human head, then identifies the possible head further in other directions. This algorithm avoids complex concepts and mathematical formulas. Its time-space complexity is much lower than other common methods used in detecting circular-like targets. This paper compares this algorithm with Hough Transform (HT) which is typical in detecting circular-like targets. It is several tens of times faster than HT, and the memory this algorithm needs is several tens of times less than HT. At the end of this paper, practice proves its good effect.","PeriodicalId":154117,"journal":{"name":"2009 International Conference on Networking and Digital Society","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A New Rapid Algorithm for Detecting Human Head\",\"authors\":\"Yangming He, Shuguang Dai\",\"doi\":\"10.1109/ICNDS.2009.110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to the features of human head which is taken by camera shooting from the top down, this paper puts forward a new and rapid algorithm for detecting human head. First, the image is binarized by threshold, then searches diameter of circular-like head area in binary image. If the diameter is in conformity with the feature of human head, then identifies the possible head further in other directions. This algorithm avoids complex concepts and mathematical formulas. Its time-space complexity is much lower than other common methods used in detecting circular-like targets. This paper compares this algorithm with Hough Transform (HT) which is typical in detecting circular-like targets. It is several tens of times faster than HT, and the memory this algorithm needs is several tens of times less than HT. At the end of this paper, practice proves its good effect.\",\"PeriodicalId\":154117,\"journal\":{\"name\":\"2009 International Conference on Networking and Digital Society\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Networking and Digital Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNDS.2009.110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Networking and Digital Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNDS.2009.110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
According to the features of human head which is taken by camera shooting from the top down, this paper puts forward a new and rapid algorithm for detecting human head. First, the image is binarized by threshold, then searches diameter of circular-like head area in binary image. If the diameter is in conformity with the feature of human head, then identifies the possible head further in other directions. This algorithm avoids complex concepts and mathematical formulas. Its time-space complexity is much lower than other common methods used in detecting circular-like targets. This paper compares this algorithm with Hough Transform (HT) which is typical in detecting circular-like targets. It is several tens of times faster than HT, and the memory this algorithm needs is several tens of times less than HT. At the end of this paper, practice proves its good effect.