A convolutional neural network for pedestrian gender recognition
作者： Choon-Boon Ng , Yong-Haur Tay , Bok-Min Goi
DOI: 10.1007/978-3-642-39065-4_67
关键词:
摘要: We propose a discriminatively-trained convolutional neural network for gender classification of pedestrians. Convolutional networks are hierarchical, multilayered which integrate feature extraction and in single framework. Using relatively straightforward architecture minimal preprocessing the images, we achieved 80.4% accuracy on dataset containing full body images pedestrians both front rear views. The performance is comparable to state-of-the-art obtained by previous methods without relying using hand-engineered extractors.
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