Intelligent human detection method based on mixed RGB and infrared images

2021 ◽  
Author(s):  
Yangyang Sun ◽  
Rufei Zhang ◽  
Ce Yang
Keyword(s):  
Detection Method ◽  
Human Detection ◽  
Infrared Images

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.

A New Moving Human Detection Method in Color Video Image

2012 ◽  
Vol 229-231 ◽  
pp. 1166-1170
Author(s):  
Tia Nai Wu ◽  
Yun Rong Wu ◽  
Yun Yu Wu
Keyword(s):  
Background Subtraction ◽  
Detection Method ◽  
Main Idea ◽  
Color Difference ◽  
Human Detection ◽  
Background Model ◽  
Video Frame ◽  
Difference Model ◽  
Background Updating ◽  
Background Image

Moving object detection is the basic of video applications such as computer vision, object recognition and tracking, surveillance security etc. Background subtraction and symmetrical differencing are the popular methods of motion detection. The main idea of them is to compare the current video frame with a specified background image or a background model or the next video frame. For background subtraction, the obtaining of initialization is crucial and many methods have been employed, so it is necessary to model background to adapt the changes of background. In this paper, the single gaussian modeling as the initialization background model combined with an improved linear alternate background updating method is proposed. And then, a novel moving human detection method which employs background subtraction and symmetrical differencing based on rgb color difference model is presented. The experimental results show that the detection method can detect moving human effectively and real-time.

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