A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
SexNet: A neural network identifies sex from human faces
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Machine Learning
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Gender and Ethnic Classification of Face Images
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Gender Classification with Support Vector Machines
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Robust Real-Time Face Detection
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
SODA-boosting and its application to gender recognition
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Gait Components and Their Application to Gender Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A study on gait-based gender classification
IEEE Transactions on Image Processing
Gender from body: a biologically-inspired approach with manifold learning
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Face-based multiple instance analysis for smart electronics billboard
Multimedia Tools and Applications
Video-Base people counting and gender recognition
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Recognizing human gender in computer vision: a survey
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Describing clothing by semantic attributes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Spatial Recurrences for Pedestrian Classification
Journal of Mathematical Imaging and Vision
A convolutional neural network for pedestrian gender recognition
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
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This paper studies the problem of recognizing gender from full body images. This problem has not been addressed before, partly because of the variant nature of human bodies and clothing that can bring tough difficulties. However, gender recognition has high application potentials, e.g. security surveillance and customer statistics collection in restaurants, supermarkets, and even building entrances. In this paper, we build a system of recognizing gender from full body images, taken from frontal or back views. Our contributions are three-fold. First, to handle the variety of human body characteristics, we represent each image by a collection of patch features, which model different body parts and provide a set of clues for gender recognition. To combine the clues, we build an ensemble learning algorithm from those body parts to recognize gender from fixed view body images (frontal or back). Second, we relax the fixed view constraint and show the possibility to train a flexible classifier for mixed view images with the almost same accuracy as the fixed view case. At last, our approach is shown to be robust to small alignment errors, which is preferred in many applications.