PyCV - A Computer Vision Package for Python Incorporating Fast Training of Face Detection
PyCV is a package of C++ and Python modules implementing various algorithms that are useful in computer vision, and augments the capabilities of OpenCV. In particular, PyCV provides implementations for:
- Fast training and selection of Haar-like features for a weak classifier [Pham2007b]. This is currently the world’s fastest method for training a face detector. It runs in just a few hours, while most existing methods run in days or weeks.
- Asymmetric Online Boosting [Pham2007a]: a variant of AdaBoost that learns incrementally using an asymmetric goal as the learning criterion.
Additionally, PyCV contains many useful modules for computer vision and machine learning, specially boosting techniques, Haar-like features, and face detection.
The package is primarily developed by Minh-Tri Pham, as part of his PhD research on face detection. This research is being carried out in the Centre for Multimedia & Network Technology (CeMNet), School of Computer Engineering, Nanyang Technological University, Singapore.
Copyright 2007 Nanyang Technological University, Singapore.
Minh-Tri Pham <firstname.lastname@example.org> – Primary author
Viet-Dung D. Hoang <email@example.com> – Contributing author
Tat-Jen Cham <firstname.lastname@example.org> – Supervising faculty
|[Pham2007a]||Minh-Tri Pham and Tat-Jen Cham. Online Learning Asymmetric Boosted Classifiers for Object Detection. In Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR‘07), Minneapolis, MN, 2007.|
|[Pham2007b]||Minh-Tri Pham and Tat-Jen Cham. Fast Training and Selection of Haar features using Statistics in Boosting-based Face Detection. In Proc. 11th IEEE International Conference on Computer Vision (ICCV‘07), Rio de Janeiro, Brazil, 2007.|