{"title":"基于边缘的嵌入式系统运动目标跟踪算法","authors":"Kai Yang, M. Sheu","doi":"10.1109/APCCAS.2016.7803920","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an image target tracking algorithm for an embedded platform. Our proposed can process 1280 × 720 resolution video sequences and provide accurate image tracking in real time. In the tracking algorithm, an adaptive local edge detection method is employed to extract the feature pixels of a tracked object. To reduce tracking errors, a region-based local binary pattern feature method was employed to describe the edge pixels of the tracked object. Finally, we implemented this object tracking method in the embedded platform to achieve real-time execution for experimental testing in a complex environment.","PeriodicalId":6495,"journal":{"name":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Edge-based moving object tracking algorithm for an embedded system\",\"authors\":\"Kai Yang, M. Sheu\",\"doi\":\"10.1109/APCCAS.2016.7803920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an image target tracking algorithm for an embedded platform. Our proposed can process 1280 × 720 resolution video sequences and provide accurate image tracking in real time. In the tracking algorithm, an adaptive local edge detection method is employed to extract the feature pixels of a tracked object. To reduce tracking errors, a region-based local binary pattern feature method was employed to describe the edge pixels of the tracked object. Finally, we implemented this object tracking method in the embedded platform to achieve real-time execution for experimental testing in a complex environment.\",\"PeriodicalId\":6495,\"journal\":{\"name\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCCAS.2016.7803920\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.2016.7803920","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge-based moving object tracking algorithm for an embedded system
In this paper, we propose an image target tracking algorithm for an embedded platform. Our proposed can process 1280 × 720 resolution video sequences and provide accurate image tracking in real time. In the tracking algorithm, an adaptive local edge detection method is employed to extract the feature pixels of a tracked object. To reduce tracking errors, a region-based local binary pattern feature method was employed to describe the edge pixels of the tracked object. Finally, we implemented this object tracking method in the embedded platform to achieve real-time execution for experimental testing in a complex environment.
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