Journal ArticleDOI
Learning local binary patterns for gender classification on real-world face images
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TLDR
This paper investigates gender recognition on real-life faces using the recently built database, the Labeled Faces in the Wild (LFW), and local Binary Patterns (LBP) is employed to describe faces, and Adaboost is used to select the discriminative LBP features.About:
This article is published in Pattern Recognition Letters.The article was published on 2012-03-01. It has received 359 citations till now. The article focuses on the topics: Local binary patterns & Face detection.read more
Citations
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Proceedings ArticleDOI
Age and gender classification using convolutional neural networks
Gil Levi,Tal Hassncer +1 more
TL;DR: This paper proposes a simple convolutional net architecture that can be used even when the amount of learning data is limited and shows that by learning representations through the use of deep-convolutional neural networks, a significant increase in performance can be obtained on these tasks.
Proceedings ArticleDOI
Unequal Representation and Gender Stereotypes in Image Search Results for Occupations
TL;DR: There is evidence for both stereotype exaggeration and systematic underrepresentation of women in search results, and it is found that people rate search results higher when they are consistent with stereotypes for a career, and shifting the representation of gender in image search results can shift people's perceptions about real-world distributions.
Journal ArticleDOI
What Else Does Your Biometric Data Reveal? A Survey on Soft Biometrics
TL;DR: An overview of soft biometrics is provided and some of the techniques that have been proposed to extract them from the image and the video data are discussed, a taxonomy for organizing and classifying soft biometric attributes is introduced, and the strengths and limitations are enumerated.
Proceedings ArticleDOI
Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns
Gil Levi,Tal Hassner +1 more
TL;DR: This work proposes novel transformations of image intensities to 3D spaces, designed to be invariant to monotonic photometric transformations, which are applied to CASIA Webface images and used to train an ensemble of multiple architecture CNNs on multiple representations.
Journal ArticleDOI
Object-Level Video Advertising: An Optimization Framework
TL;DR: New models and algorithms for object-level video advertising that aims to embed content-relevant ads within a video stream is investigated and a heuristic algorithm is developed to solve the proposed optimization problem.
References
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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.
Journal ArticleDOI
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
Yoav Freund,Robert E. Schapire +1 more
TL;DR: The model studied can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting, and it is shown that the multiplicative weight-update Littlestone?Warmuth rule can be adapted to this model, yielding bounds that are slightly weaker in some cases, but applicable to a considerably more general class of learning problems.
Journal ArticleDOI
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
Journal ArticleDOI
Robust Real-Time Face Detection
Paul A. Viola,Michael Jones +1 more
TL;DR: In this paper, a face detection framework that is capable of processing images extremely rapidly while achieving high detection rates is described. But the detection performance is limited to 15 frames per second.
Proceedings ArticleDOI
Robust real-time face detection
Paul A. Viola,Michael Jones +1 more
TL;DR: A new image representation called the “Integral Image” is introduced which allows the features used by the detector to be computed very quickly and a method for combining classifiers in a “cascade” which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions.