{"_id":"Yh5ZHQyhL3MhXbSPo","bibbaseid":"kohoksuutalaj-footsteppatternmatchingfrompressuresignalsusingsegmentalsemimarkovmodels-2004","authorIDs":[],"author_short":["Koho K Suutala J, S., T., &., R., J."],"bibdata":{"title":"Footstep pattern matching from pressure signals using segmental semi-Markov models.","type":"inProceedings","year":"2004","pages":"1609-1612","publisher":"Proc. 12th European Signal Processing Conference (EUSIPCO 2004), Vienna, Austria","id":"5f18f1a0-6961-3ed8-9ea9-427054ada8b5","created":"2019-11-19T13:01:09.533Z","file_attached":false,"profile_id":"bddcf02d-403b-3b06-9def-6d15cc293e20","group_id":"17585b85-df99-3a34-98c2-c73e593397d7","last_modified":"2019-11-19T13:46:16.710Z","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"isg:523","source_type":"inproceedings","private_publication":false,"abstract":"This paper describes experiments on recognizing footstep patterns from data produced by pressure-sensitive floor. A 100 square meter pressure-sensitive floor (EMFi floor), which is placed as a part of a smart living room, senses the changes in the pressure against its surface and produces voltage signal of the event. Recognition of footstep patterns is needed for data segmentation to be used in person tracking and identification. We have used a method based on Segmental Semi-Markov Models to detect footsteps from the floor data. The experiments described in this paper show this method to be a very powerful and robust tool for our particular application.","bibtype":"inProceedings","author":"Koho K Suutala J, Seppänen T & Röning J","bibtex":"@inProceedings{\n title = {Footstep pattern matching from pressure signals using segmental semi-Markov models.},\n type = {inProceedings},\n year = {2004},\n pages = {1609-1612},\n publisher = {Proc. 12th European Signal Processing Conference (EUSIPCO 2004), Vienna, Austria},\n id = {5f18f1a0-6961-3ed8-9ea9-427054ada8b5},\n created = {2019-11-19T13:01:09.533Z},\n file_attached = {false},\n profile_id = {bddcf02d-403b-3b06-9def-6d15cc293e20},\n group_id = {17585b85-df99-3a34-98c2-c73e593397d7},\n last_modified = {2019-11-19T13:46:16.710Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {isg:523},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {This paper describes experiments on recognizing footstep patterns from data produced by pressure-sensitive floor. A 100 square meter pressure-sensitive floor (EMFi floor), which is placed as a part of a smart living room, senses the changes in the pressure against its surface and produces voltage signal of the event. Recognition of footstep patterns is needed for data segmentation to be used in person tracking and identification. We have used a method based on Segmental Semi-Markov Models to detect footsteps from the floor data. The experiments described in this paper show this method to be a very powerful and robust tool for our particular application.},\n bibtype = {inProceedings},\n author = {Koho K Suutala J, Seppänen T & Röning J}\n}","author_short":["Koho K Suutala J, S., T., &., R., J."],"bibbaseid":"kohoksuutalaj-footsteppatternmatchingfrompressuresignalsusingsegmentalsemimarkovmodels-2004","role":"author","urls":{},"downloads":0},"bibtype":"inProceedings","creationDate":"2019-11-19T13:17:06.388Z","downloads":0,"keywords":[],"search_terms":["footstep","pattern","matching","pressure","signals","using","segmental","semi","markov","models","koho k suutala j"],"title":"Footstep pattern matching from pressure signals using segmental semi-Markov models.","year":2004}