@inproceedings{044a9e4dca584ecab31ff409bb602f04,
title = "First-person activity recognition based on three-stream deep features",
abstract = "In this paper, we present a novel three-stream deep feature fusion technique to recognize interaction-level human activities from a first-person viewpoint. Specifically, the proposed approach distinguishes human motion and camera ego-motion to focus on human{\textquoteright}s movement. The features of human and camera ego-motion information are extracted from the three-stream architecture. These features are fused by considering a relationship of human action and camera ego-motion. To validate the effectiveness of our approach, we perform experiments on UTKinect-FirstPerson dataset, and achieve state-of-the-art performance.",
keywords = "First-person activity recognition, Human-robot interaction, Robot surveillance., Three-stream deep features",
author = "Kim, {Ye Ji} and Lee, {Dong Gyu} and Lee, {Seong Whan}",
note = "Publisher Copyright: {\textcopyright} ICROS.; 18th International Conference on Control, Automation and Systems, ICCAS 2018 ; Conference date: 17-10-2018 Through 20-10-2018",
year = "2018",
month = dec,
day = "10",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "297--299",
booktitle = "International Conference on Control, Automation and Systems",
address = "United States",
}