Smriti Rani, A. Chowdhury, Andrew Gigie, T. Chakravarty, A. Pal
{"title":"利用微多普勒特征的空间分布雷达装置进行动作识别","authors":"Smriti Rani, A. Chowdhury, Andrew Gigie, T. Chakravarty, A. Pal","doi":"10.1145/3410530.3414362","DOIUrl":null,"url":null,"abstract":"Small form factor off-the shelf radar sensor nodes are being investigated for various privacy preserving non-contact sensing applications. This paper, presents a novel method, based on a system of spatially distributed radar setup(panel radar), for real time action recognition. Proposed method uses spatially distributed two single channel Continuous Wave (CW) radars to classify actions. For classification, a unique two layered classifier, is employed on novel features. Layer I performs coarse limb level classification followed by finer action detection in Layer II. For validation of the proposed system, 7 actions were targeted and data was collected for 20 people. Accuracy of 88.6 % was obtained, with a precision and recall of 0.9 and 0.89 respectively, hence proving the efficacy of this novel approach.","PeriodicalId":7183,"journal":{"name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","volume":"43 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Action recognition using spatially distributed radar setup through microdoppler signature\",\"authors\":\"Smriti Rani, A. Chowdhury, Andrew Gigie, T. Chakravarty, A. Pal\",\"doi\":\"10.1145/3410530.3414362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Small form factor off-the shelf radar sensor nodes are being investigated for various privacy preserving non-contact sensing applications. This paper, presents a novel method, based on a system of spatially distributed radar setup(panel radar), for real time action recognition. Proposed method uses spatially distributed two single channel Continuous Wave (CW) radars to classify actions. For classification, a unique two layered classifier, is employed on novel features. Layer I performs coarse limb level classification followed by finer action detection in Layer II. For validation of the proposed system, 7 actions were targeted and data was collected for 20 people. Accuracy of 88.6 % was obtained, with a precision and recall of 0.9 and 0.89 respectively, hence proving the efficacy of this novel approach.\",\"PeriodicalId\":7183,\"journal\":{\"name\":\"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3410530.3414362\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410530.3414362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Action recognition using spatially distributed radar setup through microdoppler signature
Small form factor off-the shelf radar sensor nodes are being investigated for various privacy preserving non-contact sensing applications. This paper, presents a novel method, based on a system of spatially distributed radar setup(panel radar), for real time action recognition. Proposed method uses spatially distributed two single channel Continuous Wave (CW) radars to classify actions. For classification, a unique two layered classifier, is employed on novel features. Layer I performs coarse limb level classification followed by finer action detection in Layer II. For validation of the proposed system, 7 actions were targeted and data was collected for 20 people. Accuracy of 88.6 % was obtained, with a precision and recall of 0.9 and 0.89 respectively, hence proving the efficacy of this novel approach.