Watch do: A smart IoT interaction system with object detection and gaze estimation

Jung Hwa Kim, Seung June Choi, Jin Woo Jeong

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

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.

Original languageEnglish
Article number8634883
Pages (from-to)195-204
Number of pages10
JournalIEEE Transactions on Consumer Electronics
Volume65
Issue number2
DOIs
StatePublished - May 2019

Keywords

  • Deep learning
  • gaze estimation
  • Internet of Things
  • object detection
  • smart interaction

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