Journal ArticleDOI
Head Pose Estimation in Computer Vision: A Survey
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TLDR
This paper discusses the inherent difficulties in head pose estimation and presents an organized survey describing the evolution of the field, comparing systems by focusing on their ability to estimate coarse and fine head pose and highlighting approaches well suited for unconstrained environments.Abstract:
The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.read more
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Computer Vision: Algorithms and Applications
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Proceedings ArticleDOI
Face detection, pose estimation, and landmark localization in the wild
Xiangxin Zhu,Deva Ramanan +1 more
TL;DR: It is shown that tree-structured models are surprisingly effective at capturing global elastic deformation, while being easy to optimize unlike dense graph structures, in real-world, cluttered images.
Journal ArticleDOI
HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
TL;DR: HyperFace as discussed by the authors combines face detection, landmarks localization, pose estimation and gender recognition using deep convolutional neural networks (CNNs) and achieves significant improvement in performance by fusing intermediate layers of a deep CNN using a separate CNN followed by a multi-task learning algorithm that operates on the fused features.
Proceedings ArticleDOI
OpenFace: An open source facial behavior analysis toolkit
TL;DR: OpenFace is the first open source tool capable of facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation and allows for easy integration with other applications and devices through a lightweight messaging system.
Proceedings ArticleDOI
Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization
TL;DR: AFLW provides a large-scale collection of images gathered from Flickr, exhibiting a large variety in face appearance as well as general imaging and environmental conditions, and is well suited to train and test algorithms for multi-view face detection, facial landmark localization and face pose estimation.
References
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Gradient-based learning applied to document recognition
Yann LeCun,Léon Bottou,Léon Bottou,Yoshua Bengio,Yoshua Bengio,Yoshua Bengio,Patrick Haffner +6 more
TL;DR: In this article, a graph transformer network (GTN) is proposed for handwritten character recognition, which can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters.
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TL;DR: This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition, and is designed as a text, with over 100 exercises, to benefit anyone involved in the fields of neural computation and pattern recognition.
Proceedings ArticleDOI
Rapid object detection using a boosted cascade of simple features
Paul A. Viola,Michael Jones +1 more
TL;DR: A machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates and the introduction of a new image representation called the "integral image" which allows the features used by the detector to be computed very quickly.
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Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.