3D Face Tracking Using Stereo Cameras: A Review
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Banks, Jasmine
Chandran, Vinod
Zhang, Jinglan
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This review considers previous research, regarding the background and applications of 3D face-tracking systems with a focus on stereo camera-based systems. Stereo cameras are less expensive than laser ranging systems, and they are widely available on devices such as smart phones. This review aims to spur further development and applications of face tracking in this domain. Many studies on face tracking have used concepts such as the Kanade-Lucas-Tomasi method, particle filters, tracking-learning-detecting, probability hypothesis density, mean shift/cam shift, and others. As imaging constraints are relaxed, facial tracking becomes more challenging. This review presents an exposition of the most common challenges in face tracking, such as occlusion and clutter, pose variations, changes in facial resolution, illumination variations, and facial deformation. Five forms of pose estimation are discussed: appearance template methods, detector arrays, flexible models, geometric methods, and tracking methods. Applications of the listed 3D face tracking systems are also discussed, including face modelling, film editing, access control, security, and surveillance.
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IEEE Access
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8
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© The Author(s) YEAR. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Information and computing sciences
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Computer Science, Information Systems
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Alqahtani, F; Banks, J; Chandran, V; Zhang, J, 3D Face Tracking Using Stereo Cameras: A Review, IEEE Access, 2020, 8, pp. 94373-94393