Doug Cox, Darren Fairall, Neil MacMillan, D. Marinakis, D. Meger, Saamaan Pourtavakoli, Kyle Weston
{"title":"Trajectory Inference Using a Motion Sensing Network","authors":"Doug Cox, Darren Fairall, Neil MacMillan, D. Marinakis, D. Meger, Saamaan Pourtavakoli, Kyle Weston","doi":"10.1109/CRV.2014.29","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of inferring human trajectories through an environment using low frequency, low fidelity data from a sensor network. We present a novel \"recombine\" proposal for Markov Chain construction and use the new proposal to devise a probabilistic trajectory inference algorithm that generates likely trajectories given raw sensor data. We also propose a novel, low-power, long range, 900 MHz IEEE 802.15.4 compliant sensor network that makes outdoors deployment viable. Finally, we present experimental results from our deployment at a retail environment.","PeriodicalId":385422,"journal":{"name":"2014 Canadian Conference on Computer and Robot Vision","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Canadian Conference on Computer and Robot Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2014.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper addresses the problem of inferring human trajectories through an environment using low frequency, low fidelity data from a sensor network. We present a novel "recombine" proposal for Markov Chain construction and use the new proposal to devise a probabilistic trajectory inference algorithm that generates likely trajectories given raw sensor data. We also propose a novel, low-power, long range, 900 MHz IEEE 802.15.4 compliant sensor network that makes outdoors deployment viable. Finally, we present experimental results from our deployment at a retail environment.