{"title":"监测自然场景的特征提取和跟踪的独立分量分析(ICA)方法","authors":"J. Durham, W. Torrez","doi":"10.1109/CIMSA.2004.1397217","DOIUrl":null,"url":null,"abstract":"An independent component analysis (ICA) approach to monitoring of natural scenes empirically generates robust image features for localization and tracking of potentially-occluded targets. The ICA-based empirical model utilizes statistical techniques that assist analysts in characterizing the underlying criteria that enables such feature extraction. Thus, this approach provides a basis for analyzing how the empirically generated feature localization and tracking models and related algorithms to perform their function.","PeriodicalId":102405,"journal":{"name":"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Monitoring of natural scenes for feature extraction and tracking an independent component analysis (ICA) approach\",\"authors\":\"J. Durham, W. Torrez\",\"doi\":\"10.1109/CIMSA.2004.1397217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An independent component analysis (ICA) approach to monitoring of natural scenes empirically generates robust image features for localization and tracking of potentially-occluded targets. The ICA-based empirical model utilizes statistical techniques that assist analysts in characterizing the underlying criteria that enables such feature extraction. Thus, this approach provides a basis for analyzing how the empirically generated feature localization and tracking models and related algorithms to perform their function.\",\"PeriodicalId\":102405,\"journal\":{\"name\":\"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMSA.2004.1397217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference onComputational Intelligence for Measurement Systems and Applications, 2004. CIMSA.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMSA.2004.1397217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Monitoring of natural scenes for feature extraction and tracking an independent component analysis (ICA) approach
An independent component analysis (ICA) approach to monitoring of natural scenes empirically generates robust image features for localization and tracking of potentially-occluded targets. The ICA-based empirical model utilizes statistical techniques that assist analysts in characterizing the underlying criteria that enables such feature extraction. Thus, this approach provides a basis for analyzing how the empirically generated feature localization and tracking models and related algorithms to perform their function.