Rishaad Abdoola, Yunfei Fang, Shengzhi Du, Paul Bartels, Christiaan Oosthuizen
{"title":"航空视频中基于纹理的动物分割","authors":"Rishaad Abdoola, Yunfei Fang, Shengzhi Du, Paul Bartels, Christiaan Oosthuizen","doi":"10.34257/gjreavol23is3pg1","DOIUrl":null,"url":null,"abstract":"Animal detection in aerial videos is a challenging problem due to the complex nature of the scenes involved as well as the natural ability of the animals to camouflage their environment. To assist with the detection and classification of animals for the purpose of nature conservation management, texture analysis is applied to aerial videos of wildlife scenes to segment the environment from the animals. To perform automatic wildlife surveying and animal monitoring, it is proposed to use GLCM texture segmentation to reduce the search area for animals in the aerial videos. Using the texture in the scene, the issues of a moving background and unpredictable state of the animal are avoided. The method presented is well suited to implementation on a UAV as it is easily parallelizable.","PeriodicalId":93101,"journal":{"name":"Global journal of medical research","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Texture based Animal Segmentation in Aerial Videos\",\"authors\":\"Rishaad Abdoola, Yunfei Fang, Shengzhi Du, Paul Bartels, Christiaan Oosthuizen\",\"doi\":\"10.34257/gjreavol23is3pg1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Animal detection in aerial videos is a challenging problem due to the complex nature of the scenes involved as well as the natural ability of the animals to camouflage their environment. To assist with the detection and classification of animals for the purpose of nature conservation management, texture analysis is applied to aerial videos of wildlife scenes to segment the environment from the animals. To perform automatic wildlife surveying and animal monitoring, it is proposed to use GLCM texture segmentation to reduce the search area for animals in the aerial videos. Using the texture in the scene, the issues of a moving background and unpredictable state of the animal are avoided. The method presented is well suited to implementation on a UAV as it is easily parallelizable.\",\"PeriodicalId\":93101,\"journal\":{\"name\":\"Global journal of medical research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global journal of medical research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34257/gjreavol23is3pg1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global journal of medical research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34257/gjreavol23is3pg1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Texture based Animal Segmentation in Aerial Videos
Animal detection in aerial videos is a challenging problem due to the complex nature of the scenes involved as well as the natural ability of the animals to camouflage their environment. To assist with the detection and classification of animals for the purpose of nature conservation management, texture analysis is applied to aerial videos of wildlife scenes to segment the environment from the animals. To perform automatic wildlife surveying and animal monitoring, it is proposed to use GLCM texture segmentation to reduce the search area for animals in the aerial videos. Using the texture in the scene, the issues of a moving background and unpredictable state of the animal are avoided. The method presented is well suited to implementation on a UAV as it is easily parallelizable.