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Title: Autonomous Face Detection and Tracking Using Quadrotor UAV
Authors: Karahan, M.
Kurt, Hamza
Kasnakoğlu, Coşku
Keywords: Cameras
face detection
face tracking
feature tracking
optical flow
Quadrotorrobot vision systems
weak classifier
Issue Date: Oct-2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Karahan, M., Kurt, H., and Kasnakoglu, C. (2020, October). Autonomous Face Detection and Tracking Using Quadrotor UAV. In 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-4). IEEE.
Abstract: In this paper, human face detection and tracking system with a camera of the Quadrotor UAV is proposed. During flight, Quadrotor takes photos of the human face, records videos and sends these photos and videos to the computer with Wi-fi connection. Face detection algorithm detects human face using Viola Jones algorithm. Face detection algorithm can detect multiple faces at the same time. Face tracking algorithm identifies feature points of the face in first frame and track these features in following frames in a video recorded by the Quadrotor UAV's camera. Face detection and face tracking algorithms' performances are evaluated by using photos and videos of the human faces. It could be interpreted that face detection algorithm successfully detect single and multiple faces and face tracking algorithm is competent to track the human face. © 2020 IEEE.
ISBN: 978-172819090-7
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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