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Watch & Do: A Smart IoT Interaction System With Object Detection and Gaze Estimation

Authors
Kim, Jung-HwaChoi, Seung-JuneJeong, Jin-Woo
Issue Date
May-2019
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Deep learning; gaze estimation; Internet of Things; object detection; smart interaction
Citation
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, v.65, no.2, pp 195 - 204
Pages
10
Journal Title
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
Volume
65
Number
2
Start Page
195
End Page
204
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/25544
DOI
10.1109/TCE.2019.2897758
ISSN
0098-3063
1558-4127
Abstract
The Internet of Things (IoT) attempts to help people access Internet-connected devices, applications, and services anytime and anywhere. However, how providing an efficient and intuitive method of interaction between people and IoT devices is still an open challenge. In this paper, we propose a novel interaction system called Watch & Do, where users can control an IoT device by gazing at it and doing simple gestures. The proposed system mainly consists of: 1) object detection module; 2) gaze estimation module; 3) hand gesture recognition module; and 4) IoT controller module. The target device is identified by various deep learning-based gaze estimation and object detection techniques. Afterwards, hand gesture recognition is applied to generate an IoT device control command which is transmitted to the IoT platform. The experimental results and case studies demonstrate the feasibility of the proposed system and imply the future research directions.
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