A convolutional neural network cascade for face detection
- 1 June 2015
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 5325-5334
- https://doi.org/10.1109/cvpr.2015.7299170
Abstract
In real-world face detection, large visual variations, such as those due to pose, expression, and lighting, demand an advanced discriminative model to accurately differentiate faces from the backgrounds. Consequently, effective models for the problem tend to be computationally prohibitive. To address these two conflicting challenges, we propose a cascade architecture built on convolutional neural networks (CNNs) with very powerful discriminative capability, while maintaining high performance. The proposed CNN cascade operates at multiple resolutions, quickly rejects the background regions in the fast low resolution stages, and carefully evaluates a small number of challenging candidates in the last high resolution stage. To improve localization effectiveness, and reduce the number of candidates at later stages, we introduce a CNN-based calibration stage after each of the detection stages in the cascade. The output of each calibration stage is used to adjust the detection window position for input to the subsequent stage. The proposed method runs at 14 FPS on a single CPU core for VGA-resolution images and 100 FPS using a GPU, and achieves state-of-the-art detection performance on two public face detection benchmarks.Keywords
This publication has 16 references indexed in Scilit:
- CaffePublished by Association for Computing Machinery (ACM) ,2014
- Efficient Boosted Exemplar-Based Face DetectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Face Detection without Bells and WhistlesLecture Notes in Computer Science, 2014
- Detecting and Aligning Faces by Image RetrievalPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Multiresolution Models for Object DetectionLecture Notes in Computer Science, 2010
- Rapid object detection using a boosted cascade of simple featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- An extended set of Haar-like features for rapid object detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- A neural architecture for fast and robust face detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Neural network-based face detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1996
- Original approach for the localisation of objects in imagesIEE Proceedings - Vision, Image, and Signal Processing, 1994