Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing. Gong, J., Zhang, Y., Zhou, X., & Yang, X. In Proceedings of the Annual ACM Symposium on User Interface Software and Technology (UIST), pages 553-563, 10, 2017. ACM Press. ![Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex We present Pyro, a micro thumb-tip gesture recognition technique based on thermal infrared signals radiating from the fingers. Pyro uses a compact, low-power passive sensor, making it suitable for wearable and mobile applications. To demonstrate the feasibility of Pyro, we developed a self-contained prototype consisting of the infrared pyroelectric sensor, a custom sensing circuit, and software for signal processing and machine learning. A ten-participant user study yielded a 93.9% cross-validation accuracy and 84.9% leave-one-session-out accuracy on six thumb-tip gestures. Subsequent lab studies demonstrated Pyro's robustness to varying light conditions, hand temperatures, and background motion. We conclude by discussing the insights we gained from this work and future research questions.
@inProceedings{
title = {Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing},
type = {inProceedings},
year = {2017},
identifiers = {[object Object]},
keywords = {auracle,hci,infrared,sensors,user-interface,wearable},
pages = {553-563},
websites = {http://dx.doi.org/10.1145/3126594.3126615},
month = {10},
publisher = {ACM Press},
id = {4c35f3c9-5cd3-3faa-88f6-21a422b220f3},
created = {2018-07-12T21:31:27.006Z},
file_attached = {false},
profile_id = {f954d000-ce94-3da6-bd26-b983145a920f},
group_id = {b0b145a3-980e-3ad7-a16f-c93918c606ed},
last_modified = {2018-07-12T21:31:27.006Z},
read = {false},
starred = {false},
authored = {false},
confirmed = {true},
hidden = {false},
citation_key = {gong:pyro},
source_type = {inproceedings},
private_publication = {false},
abstract = {We present Pyro, a micro thumb-tip gesture recognition technique based on thermal infrared signals radiating from the fingers. Pyro uses a compact, low-power passive sensor, making it suitable for wearable and mobile applications. To demonstrate the feasibility of Pyro, we developed a self-contained prototype consisting of the infrared pyroelectric sensor, a custom sensing circuit, and software for signal processing and machine learning. A ten-participant user study yielded a 93.9% cross-validation accuracy and 84.9% leave-one-session-out accuracy on six thumb-tip gestures. Subsequent lab studies demonstrated Pyro's robustness to varying light conditions, hand temperatures, and background motion. We conclude by discussing the insights we gained from this work and future research questions.},
bibtype = {inProceedings},
author = {Gong, Jun and Zhang, Yang and Zhou, Xia and Yang, Xing-Dong},
booktitle = {Proceedings of the Annual ACM Symposium on User Interface Software and Technology (UIST)}
}
Downloads: 0
{"_id":"Z4g5XJvyuT8dvYDwm","bibbaseid":"gong-zhang-zhou-yang-pyrothumbtipgesturerecognitionusingpyroelectricinfraredsensing-2017","downloads":0,"creationDate":"2019-02-15T15:14:59.093Z","title":"Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing","author_short":["Gong, J.","Zhang, Y.","Zhou, X.","Yang, X."],"year":2017,"bibtype":"inProceedings","biburl":null,"bibdata":{"title":"Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing","type":"inProceedings","year":"2017","identifiers":"[object Object]","keywords":"auracle,hci,infrared,sensors,user-interface,wearable","pages":"553-563","websites":"http://dx.doi.org/10.1145/3126594.3126615","month":"10","publisher":"ACM Press","id":"4c35f3c9-5cd3-3faa-88f6-21a422b220f3","created":"2018-07-12T21:31:27.006Z","file_attached":false,"profile_id":"f954d000-ce94-3da6-bd26-b983145a920f","group_id":"b0b145a3-980e-3ad7-a16f-c93918c606ed","last_modified":"2018-07-12T21:31:27.006Z","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"gong:pyro","source_type":"inproceedings","private_publication":false,"abstract":"We present Pyro, a micro thumb-tip gesture recognition technique based on thermal infrared signals radiating from the fingers. Pyro uses a compact, low-power passive sensor, making it suitable for wearable and mobile applications. To demonstrate the feasibility of Pyro, we developed a self-contained prototype consisting of the infrared pyroelectric sensor, a custom sensing circuit, and software for signal processing and machine learning. A ten-participant user study yielded a 93.9% cross-validation accuracy and 84.9% leave-one-session-out accuracy on six thumb-tip gestures. Subsequent lab studies demonstrated Pyro's robustness to varying light conditions, hand temperatures, and background motion. We conclude by discussing the insights we gained from this work and future research questions.","bibtype":"inProceedings","author":"Gong, Jun and Zhang, Yang and Zhou, Xia and Yang, Xing-Dong","booktitle":"Proceedings of the Annual ACM Symposium on User Interface Software and Technology (UIST)","bibtex":"@inProceedings{\n title = {Pyro: Thumb-Tip Gesture Recognition Using Pyroelectric Infrared Sensing},\n type = {inProceedings},\n year = {2017},\n identifiers = {[object Object]},\n keywords = {auracle,hci,infrared,sensors,user-interface,wearable},\n pages = {553-563},\n websites = {http://dx.doi.org/10.1145/3126594.3126615},\n month = {10},\n publisher = {ACM Press},\n id = {4c35f3c9-5cd3-3faa-88f6-21a422b220f3},\n created = {2018-07-12T21:31:27.006Z},\n file_attached = {false},\n profile_id = {f954d000-ce94-3da6-bd26-b983145a920f},\n group_id = {b0b145a3-980e-3ad7-a16f-c93918c606ed},\n last_modified = {2018-07-12T21:31:27.006Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {gong:pyro},\n source_type = {inproceedings},\n private_publication = {false},\n abstract = {We present Pyro, a micro thumb-tip gesture recognition technique based on thermal infrared signals radiating from the fingers. Pyro uses a compact, low-power passive sensor, making it suitable for wearable and mobile applications. To demonstrate the feasibility of Pyro, we developed a self-contained prototype consisting of the infrared pyroelectric sensor, a custom sensing circuit, and software for signal processing and machine learning. A ten-participant user study yielded a 93.9% cross-validation accuracy and 84.9% leave-one-session-out accuracy on six thumb-tip gestures. Subsequent lab studies demonstrated Pyro's robustness to varying light conditions, hand temperatures, and background motion. We conclude by discussing the insights we gained from this work and future research questions.},\n bibtype = {inProceedings},\n author = {Gong, Jun and Zhang, Yang and Zhou, Xia and Yang, Xing-Dong},\n booktitle = {Proceedings of the Annual ACM Symposium on User Interface Software and Technology (UIST)}\n}","author_short":["Gong, J.","Zhang, Y.","Zhou, X.","Yang, X."],"urls":{"Website":"http://dx.doi.org/10.1145/3126594.3126615"},"bibbaseid":"gong-zhang-zhou-yang-pyrothumbtipgesturerecognitionusingpyroelectricinfraredsensing-2017","role":"author","keyword":["auracle","hci","infrared","sensors","user-interface","wearable"],"downloads":0},"search_terms":["pyro","thumb","tip","gesture","recognition","using","pyroelectric","infrared","sensing","gong","zhang","zhou","yang"],"keywords":["auracle","hci","infrared","sensors","user-interface","wearable"],"authorIDs":[]}