@inproceedings{a341732e63f34ee98900b8051227dc87,
title = "Fast human detection using Gaussian particle swarm optimization",
abstract = "Human detection is a challenging task in many fields because it is difficult to detect humans due to their varying appearance and posture. The evaluation speed of the method is important as well as its accuracy. In this paper, we propose a novel method using Gaussian Particle Swarm Optimization (Gaussian-PSO) for human detection with the Histograms of Oriented Gradients (HOG) feature to achieve a fast and accurate performance. Keeping the robustness of HOG feature on human detection, we raise the process speed in detection process so that it can be used for real-time applications. These advantages are given by a simple process which needs only one linear-SVM classifier with HOG features and Gaussian-PSO procedure.",
keywords = "Gaussian-PSO, Histograms of Oriented Gradients (HOG), Human Detection, Particle Swarm Optimization (PSO), Pedestrian Detection",
author = "An, {Sung Tae} and Kim, {Jeong Jung} and Lee, {Joon Woo} and Lee, {Ju Jang}",
year = "2011",
doi = "10.1109/DEST.2011.5936614",
language = "English",
isbn = "9781457708725",
series = "IEEE International Conference on Digital Ecosystems and Technologies",
pages = "143--146",
booktitle = "Proceedings of the 5th IEEE International Conference on Digital Ecosystems and Technologies, DEST 2011",
note = "5th IEEE International Conference on Digital Ecosystems and Technologies, DEST 2011 ; Conference date: 31-05-2011 Through 03-06-2011",
}