Study on Detection of Human Motion Using a RGB Color Space Shadow Method with Mechanics Properties

2013 ◽  
Vol 703 ◽  
pp. 304-307
Author(s):  
Bao Dong Yan ◽  
Ying Yu
Keyword(s):  
Object Detection ◽  
Detection Threshold ◽  
Color Space ◽  
Detection Algorithm ◽  
Human Motion ◽  
Image Sequences ◽  
Shadow Detection ◽  
Motion Feature ◽  
Human Motion Detection ◽  
Rgb Color Space

The aim of human mechanics is to reveal the mechanics properties of human motion. Especially, the purpose of human motion detection is detecting the moving people from continuous image sequences, extracting human body segments and then getting motion feature. The paper presents a shadow detection algorithm based on covariance difference operator based RGB color space and discusses its mechanics properties. The presented algorithm includes four steps: object detection, suspected shadow detection, shadow detection and post processing. The presented algorithm of adaptive shadow detection threshold is adopted to suppress the effect of shadow in moving object detection more effectively. The experiment results show the algorithm presented in this paper can detect shadow effectively.

A HSV Space Shadow Method Based Human Motion Detection

2013 ◽  
Vol 706-708 ◽  
pp. 597-600
Author(s):  
Hui Dang
Keyword(s):  
Color Space ◽  
Human Action ◽  
Human Motion ◽  
Shadow Detection ◽  
Fundamental Issue ◽  
Color Information ◽  
Shadow Method ◽  
Hsv Color Space ◽  
Human Motion Detection ◽  
Action Analysis

Human Action Analysis is a fundamental issue that can be applied to different application domains. In this paper, we present a HSV color space based shadow method. The process of the algorithm mainly includes three steps: motional object detection, shadow detection of the object and post-processing. In order to enhance the accuracy of shadow detection, the value of and in the method can be select elaborately. The experiment result indicates the presented algorithm can detect shadow effectively and make full use of the color information.

OBJECTS DETECTION FROM AN IMAGE USING MATLAB

2020 ◽  
Vol 70 (4) ◽  
Author(s):  
Sherif Sherif ◽  
Jordan Kralev ◽  
Tsonyo Slavov
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Embedded Systems ◽  
Object Detection ◽  
Color Space ◽  
Detection Algorithm ◽  
Color Space Conversion ◽  
Intensity Images ◽  
Objects Detection

Objects detection from a cluttered scene is one of the main tasks in computer vision. A lot of research has focused on the optimization of this process by using machine learning, where creating algorithms with specific instructions for solving a problem is not applicable. Most of embedded systems for detection object are based on algorithms using monochrome (intensity) images. Therefore, in the article are created models for color space conversion from images and the main stages of the object detection algorithm are discussed, as well as the functions through which this is done in MATLAB.

An Improved Approach of Color Edge Detection Based on Robustness of Cell Neural Network

2011 ◽  
Vol 403-408 ◽  
pp. 1879-1882
Author(s):  
Qing Ling Jiang
Keyword(s):  
Neural Network ◽  
Edge Detection ◽  
Color Image ◽  
Color Space ◽  
Robustness Analysis ◽  
Detection Algorithm ◽  
Edge Extraction ◽  
Image Edge Detection ◽  
Image Edge ◽  
Rgb Color Space

For the disadvantage of cell neural network (CNN) method which can not directly deal with color images, we present a new color image edge detection algorithm according to CNN model. Through robustness analysis for CNN template, a CNN theorem be carried out which can compute in the RGB color space. The experimental results show that our approach can effectively carry out edge extraction and locates accurately.

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