Fast human detection using Gaussian Particle Swarm Optimization

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.

[1]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[2]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[3]  Keiichiro Yasuda,et al.  Parameter tuning of fixed structure controller for power system stability enhancement , 2002, IEEE/PES Transmission and Distribution Conference and Exhibition.

[4]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[5]  James Kennedy,et al.  Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[6]  Lehrstuhl für Elektrische,et al.  Gaussian swarm: a novel particle swarm optimization algorithm , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[7]  Liyan Zhang,et al.  Robust PID controller design using particle swarm optimizer , 2003, Proceedings of the 2003 IEEE International Symposium on Intelligent Control.

[8]  Mei-Chen Yeh,et al.  Fast Human Detection Using a Cascade of Histograms of Oriented Gradients , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[9]  Yoshikazu Fukuyama,et al.  A particle swarm optimization for reactive power and voltage control in electric power systems , 1999, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).