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Killing-Time Detection from Smartphone Screenshots

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Yung-Ju ChangAuthors Info & Claims

UbiComp/ISWC '21 Adjunct: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers

Pages 15 - 16

https://doi.org/10.1145/3460418.3479295

Published: 24 September 2021 Publication History

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Abstract

Finding good moments to deliver interruptions has drawn research attention. Since users have attention surplus at these moments, killing-time is considered one such a kind of moment. However, detection on killing-time has been under researched. In this paper, we propose a screenshot-based killing-time detection with deep learning. Our model achieves an accuracy 79.71%, recall 90.24%, precision 84.51%, and AUROC 65.50%. This suggests that using screenshots to detect users’ kill time behavior on smartphones is a promising approach. It may be worthwhile to investigate how the fusion of screenshots and sensor data can further improve detection.

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Chen YLee YKao KTsai JLiang EChiu WShih FChang Y(2023)Are You Killing Time? Predicting Smartphone Users’ Time-killing Moments via Fusion of Smartphone Sensor Data and ScreenshotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580689(1-19)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580689

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September 2021

711 pages

ISBN:9781450384612

DOI:10.1145/3460418

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 24 September 2021

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UbiComp '21: The 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 21 - 26, 2021

Virtual, USA

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Chen YLee YKao KTsai JLiang EChiu WShih FChang Y(2023)Are You Killing Time? Predicting Smartphone Users’ Time-killing Moments via Fusion of Smartphone Sensor Data and ScreenshotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580689(1-19)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580689

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Are You Killing Time? Predicting Smartphone Users’ Time-killing Moments via Fusion of Smartphone Sensor Data and Screenshots

Real-time anomaly detection on time series of industrial furnaces: A comparison of autoencoder architectures

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