An Approach to Adaptive Pedestrian Detection and Classification in Infrared Images Based on Human Visual Mechanism and Support Vector Machine

2017 ◽  
Vol 43 (8) ◽  
pp. 3951-3963 ◽  
Author(s):  
Rajkumar Soundrapandiyan ◽  
P. V. S. S. R. Chandra Mouli
Keyword(s):  
Support Vector Machine ◽  
Pedestrian Detection ◽  
Support Vector ◽  
Infrared Images ◽  
Visual Mechanism ◽  
Human Visual Mechanism

Pedestrian Crowd Detection Based Unmanned Aerial Vehicle Infrared Imagery

2017 ◽  
Vol 873 ◽  
pp. 347-352
Author(s):  
Yong Hao Xiao ◽  
Hong Zhen
Keyword(s):  
Computer Vision ◽  
Support Vector Machine ◽  
Human Detection ◽  
Support Vector ◽  
Infrared Images ◽  
Histogram Of Oriented Gradient ◽  
Detection Approach ◽  
Aerial Vehicle ◽  
Geometric Filtering ◽  
Pedestrian Crowd

Human detection is a keyproblem in computer vision. Recently, some research has been focusing on the detection ofpedestrianusing infrared images. The infrared images have outstanding merit. It depends only on object's temperature, but not on color or texture. In this paper, the pedestrian crowd detection approach is proposed. The approach is compose of ROI blocks extraction and crowd block recognition. ROI blocks can be extracted with circle gradient operator and weighted geometric filtering. Crowd blocks are recognized by support vector machine, which combines histogram of oriented gradient and circle gradient. The experimental results show thatthe approach works effectively in different scenes.

Associated evolution of a support vector machine-based classifier for pedestrian detection

2009 ◽  
Vol 179 (8) ◽  
pp. 1070-1077 ◽  
Author(s):  
X.B. Cao ◽  
Y.W. Xu ◽  
D. Chen ◽  
H. Qiao
Keyword(s):  
Support Vector Machine ◽  
Pedestrian Detection ◽  
Support Vector
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