Florian Grützmacher, Johann-Peter Wolff, C. Haubelt
{"title":"Exploiting thread-level parallelism in template-based gesture recognition with dynamic time warping","authors":"Florian Grützmacher, Johann-Peter Wolff, C. Haubelt","doi":"10.1145/2790044.2790050","DOIUrl":null,"url":null,"abstract":"Mobile devices have become ubiquitous, powerful computing devices. While their use scenarios require new input methods, their typical many-core computing architectures allow for new ways to implement these input methods. In this paper the suitability of many-core digital signal processors for online hand gesture recognition is evaluated. To this end, a system consisting of a data glove with three accelerometers and a many-core digital signal processor board is presented. Experiments assess realtime properties in hand gesture recognition on the many-core processing platform.","PeriodicalId":351171,"journal":{"name":"Proceedings of the 2nd international Workshop on Sensor-based Activity Recognition and Interaction","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd international Workshop on Sensor-based Activity Recognition and Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2790044.2790050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Mobile devices have become ubiquitous, powerful computing devices. While their use scenarios require new input methods, their typical many-core computing architectures allow for new ways to implement these input methods. In this paper the suitability of many-core digital signal processors for online hand gesture recognition is evaluated. To this end, a system consisting of a data glove with three accelerometers and a many-core digital signal processor board is presented. Experiments assess realtime properties in hand gesture recognition on the many-core processing platform.