Proceedings ArticleDOI
Joint Haar-like features for face detection
T. Mita,Toshimitsu Kaneko,O. Hori +2 more
- Vol. 2, pp 1619-1626
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TLDR
Experimental results show that the proposed joint Haar-like feature for detecting faces in images yields higher classification performance than Viola and Jones' detector; which uses a single feature for each weak classifier.Abstract:
In this paper, we propose a new distinctive feature, called joint Haar-like feature, for detecting faces in images. This is based on co-occurrence of multiple Haar-like features. Feature co-occurrence, which captures the structural similarities within the face class, makes it possible to construct an effective classifier. The joint Haar-like feature can be calculated very fast and has robustness against addition of noise and change in illumination. A face detector is learned by stagewise selection of the joint Haar-like features using AdaBoost. A small number of distinctive features achieve both computational efficiency and accuracy. Experimental results with 5, 676 face images and 30,000 nonface images show that our detector yields higher classification performance than Viola and Jones' detector; which uses a single feature for each weak classifier. Given the same number of features, our method reduces the error by 37%. Our detector is 2.6 times as fast as Viola and Jones' detector to achieve the same performanceread more
Citations
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A Survey of Recent Advances in Face Detection
Cha Zhang,Zhengyou Zhang +1 more
TL;DR: This technical report surveys the recent advances in face detection for the past decade and surveys the various techniques according to how they extract features and what learning algorithms are adopted.
Patent
Information processing apparatus, information processing method and program
Fuminori Homma,Tatsushi Nashida +1 more
TL;DR: In this article, a method for modifying an image is presented, which consists of displaying an image, the image comprising a portion of an object; determining if an edge of the object is in a location within the portion; and detecting movement in a member direction, of an operating member with respect to the edge.
Book ChapterDOI
Face detection based on multi-block LBP representation
TL;DR: This paper presents the use of a new set of distinctive rectangle features, called Multi-block Local Binary Patterns (MB-LBP), for face detection, which encodes rectangular regions' intensities by local binary pattern operator, and the resulting binary patterns can describe diverse local structures of images.
Journal ArticleDOI
High-Performance Rotation Invariant Multiview Face Detection
TL;DR: A series of innovative methods are proposed to construct a high-performance rotation invariant multiview face detector, including the width-first-search (WFS) tree detector structure, the vector boosting algorithm for learning vector-output strong classifiers, the domain-partition-based weak learning method, the sparse feature in granular space, and the heuristic search for sparse feature selection.
Journal ArticleDOI
A survey on face detection in the wild
TL;DR: The recent advances in real-world face detection techniques are surveyed, beginning with the seminal Viola-Jones face detector methodology and are roughly categorized into two general schemes: rigid templates, learned mainly via boosting based methods or by the application of deep neural networks, and deformable models that describe the face by its parts.
References
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Proceedings ArticleDOI
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TL;DR: This paper introduces a novel set of rotated Haar-like features that significantly enrich the simple features of Viola et al. scheme based on a boosted cascade of simple feature classifiers.