{"title":"利用粒子滤波和DCT特征跟踪目标","authors":"Cong Lin, Chi-Man Pun","doi":"10.2991/CSE.2013.39","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed an object tracking method for video stream based on conventional particle filter. Feature vectors are extracted from coefficient matrices of Discrete Cosine Transform (DCT). The feature, as experiment showed, is very robust to occlusion and rotation and it is not sensitive to scale changes. The proposed method is efficient enough to be used in a real-time application. The experiment is carried out on some common used datasets in literature. The result is satisfied and showed the estimated trace follows the target object very closely.","PeriodicalId":6838,"journal":{"name":"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)","volume":"1 1","pages":"169-171"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Tracking Object Using Particle Filter and DCT Features\",\"authors\":\"Cong Lin, Chi-Man Pun\",\"doi\":\"10.2991/CSE.2013.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we proposed an object tracking method for video stream based on conventional particle filter. Feature vectors are extracted from coefficient matrices of Discrete Cosine Transform (DCT). The feature, as experiment showed, is very robust to occlusion and rotation and it is not sensitive to scale changes. The proposed method is efficient enough to be used in a real-time application. The experiment is carried out on some common used datasets in literature. The result is satisfied and showed the estimated trace follows the target object very closely.\",\"PeriodicalId\":6838,\"journal\":{\"name\":\"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)\",\"volume\":\"1 1\",\"pages\":\"169-171\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/CSE.2013.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 24th International Conference on Computational Science and Engineering (CSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/CSE.2013.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tracking Object Using Particle Filter and DCT Features
In this paper, we proposed an object tracking method for video stream based on conventional particle filter. Feature vectors are extracted from coefficient matrices of Discrete Cosine Transform (DCT). The feature, as experiment showed, is very robust to occlusion and rotation and it is not sensitive to scale changes. The proposed method is efficient enough to be used in a real-time application. The experiment is carried out on some common used datasets in literature. The result is satisfied and showed the estimated trace follows the target object very closely.