@article{ref1,
title="Fast human detection using a novel boosted cascading structure with meta stages",
journal="IEEE transactions on image processing",
year="2008",
author="Chen, Yu-ting and Chen, Chu-song",
volume="17",
number="8",
pages="1452-1464",
abstract="We propose a method that can detect humans in a single image based on a novel cascaded structure. In our approach, both intensity-based rectangle features and gradient-based 1-D features are employed in the feature pool for weak-learner selection. The Real AdaBoost algorithm is used to select critical features from a combined feature set and learn the classifiers from the training images for each stage of the cascaded structure. Instead of using the standard boosted cascade, the proposed method employs a novel cascaded structure that exploits both the stage-wise classification information and the interstage cross-reference information. We introduce meta-stages to enhance the detection performance of a boosted cascade. Experiment results show that the proposed approach achieves high detection accuracy and efficiency.<p />",
language="",
issn="1057-7149",
doi="10.1109/TIP.2008.926152",
url="http://dx.doi.org/10.1109/TIP.2008.926152"
}