{"title":"惯性传感器信号的压缩信号表示","authors":"C. Amma, H. Volk, Tanja Schultz","doi":"10.1145/2494091.2494140","DOIUrl":null,"url":null,"abstract":"We present and evaluate a method to generate a compressed representation of multi-dimensional inertial sensor signals using a piecewise linear approximation. The representation can be computed on small sensor nodes and thus allows for a reduction of the amount of data that needs to be transmitted to the main processing node. On an existing gesture database, we present the compression rate that is reached and evaluate the quality of the representation in terms of the accuracy reached for gesture classification. We compare the results to our baseline system using a simpler approach for data reduction.","PeriodicalId":220524,"journal":{"name":"Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication","volume":"12 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Compressed signal representation for inertial sensor signals\",\"authors\":\"C. Amma, H. Volk, Tanja Schultz\",\"doi\":\"10.1145/2494091.2494140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present and evaluate a method to generate a compressed representation of multi-dimensional inertial sensor signals using a piecewise linear approximation. The representation can be computed on small sensor nodes and thus allows for a reduction of the amount of data that needs to be transmitted to the main processing node. On an existing gesture database, we present the compression rate that is reached and evaluate the quality of the representation in terms of the accuracy reached for gesture classification. We compare the results to our baseline system using a simpler approach for data reduction.\",\"PeriodicalId\":220524,\"journal\":{\"name\":\"Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication\",\"volume\":\"12 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2494091.2494140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2494091.2494140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compressed signal representation for inertial sensor signals
We present and evaluate a method to generate a compressed representation of multi-dimensional inertial sensor signals using a piecewise linear approximation. The representation can be computed on small sensor nodes and thus allows for a reduction of the amount of data that needs to be transmitted to the main processing node. On an existing gesture database, we present the compression rate that is reached and evaluate the quality of the representation in terms of the accuracy reached for gesture classification. We compare the results to our baseline system using a simpler approach for data reduction.