A Global-Motion Analysis Method via Rough-Set-Based Video Pre-classification

2005 ◽  
pp. 323-332 ◽  
Author(s):  
Zhe Yuan ◽  
Yu Wu ◽  
Guoyin Wang ◽  
Jianbo Li
Keyword(s):  
Motion Analysis ◽  
Rough Set ◽  
Analysis Method ◽  
Global Motion ◽  
Global Motion Analysis

Supervised Method for Congestion Detection at Entry and Exit Corridors of Public Places

2020 ◽  
pp. 2150019
Author(s):  
Manasi Pathade ◽  
Madhuri Khambete
Keyword(s):  
Motion Analysis ◽  
Continuous Monitoring ◽  
Complex Dynamics ◽  
Automatic Detection ◽  
Global Motion ◽  
Entry And Exit ◽  
Public Places ◽  
Congestion Detection ◽  
Crowded Scenes ◽  
Global Motion Analysis

Continuous monitoring and automatic detection of crowd activities is extremely helpful for management at public places to avoid any possible disaster. Analysis of crowded scene is a critical task as it typically involves poor resolution of objects, occlusions and complex dynamics. In this paper, we propose a novel, systematic and generalized method based on global motion analysis of people to detect Congestion situation in crowded scenes at entry/exit corridors. Our approach is tested on video footages acquired from surveillance cameras installed at exit corridors of public places. The results show the expediency of our approach.

Novel 3-Dimensional Motion Analysis Method for Measuring the Lumbar Spine Range of Motion

Spine ◽  
2013 ◽  
Vol 38 (21) ◽  
pp. E1327-E1333 ◽  
Author(s):  
Michio Tojima ◽  
Naoshi Ogata ◽  
Arito Yozu ◽  
Masahiko Sumitani ◽  
Nobuhiko Haga
Keyword(s):  
Lumbar Spine ◽  
Range Of Motion ◽  
Motion Analysis ◽  
Analysis Method ◽  
3 Dimensional

A Noninvasive, Three-Dimensional Spinal Motion Analysis Method

Spine ◽  
1997 ◽  
Vol 22 (17) ◽  
pp. 1996-2000 ◽  
Author(s):  
Tae-Hong Lim ◽  
Jason C. Eck ◽  
Howard S. An ◽  
Linda M. McGrady ◽  
Gerald F. Harris ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Three Dimensional ◽  
Analysis Method ◽  
Spinal Motion

A Novel Rough Set-Based Method of Combined Attributes Analysis

2012 ◽  
Vol 546-547 ◽  
pp. 1404-1408
Author(s):  
Ye Li ◽  
Bing Lu
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Analysis Method ◽  
Theory Analysis ◽  
Attribute Analysis ◽  
Single Attribute

Aiming at improving the disvantage of single attribute analysis in rough set, the problem of combined attributes analysis is researched in this paper. The single attribute ayalysis only consider the effect of the factor itself on the decison-making but neglect the interaction between multy-attributes influencing the results of the decision-making. So a new combined attributes weighting is presented in this paper.On this basis,a novel analysis method of combined attributes in rough set is proposed. The experiment and theory analysis shows that the new approch is feasible. In addition,it can mine the latent effect on decision making of combined attribute and make up for the shortage brought by single attribute analysis .

An Application of Rough Set Analysis toa Psycho-Physiological Study - Assessing the RelationBetween Psychological Scale and Immunological Biomarker

2009 ◽  
Vol 13 (4) ◽  
pp. 352-359
Author(s):  
Shusaku Nomura ◽  
◽  
Yasuo Kudo ◽  
Keyword(s):  
Rough Set ◽  
Linear Correlation ◽  
Mental Stress ◽  
Rough Set Theory ◽  
Physiological State ◽  
Mental States ◽  
Psychological State ◽  
Analysis Method ◽  
Psychological Scale ◽  
The Relationship

This study aims at an application of rough set theory to illustrate the relationship between human psychological and physiological states. Recent behavioral medicine studies have revealed that various human secretory substances change according to mental states. These substances, the hormones and immune substances, show temporal increase against mental stress. Thus, it is frequently introduced as biomarkers of mental stress. The relationship between these biomarkers and human chronic stresses or daily mental states was also suggested in the previous studies. However the results of these studies were sometimes inconsistent with each other. Some technical reasons were indicated for this discrepancy. Among that, we focused on the analysis technique investigating the relationship between human psychological state, i.e., scores of a psychological scale, and physiological state, i.e., level of the secretory biomarkers. In this paper, we introduced Rough Set analysis method instead of using a conventional linear correlation analysis method. In the experiment, the salivary secretory immunoglobulin A (IgA), which is a major stress biomarker, of 20 male students was assessed before and after a short-term stressful mental workload. Also, 65 items of psychological mood scale was assessed as a psychological index. The result showed that some items strongly related with the change in the IgA, while no significant linear correlation was obtained among them.

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