[Imageworld] TSMC-B special issue on Video-based Gait Analysis and Applications

[Liang Wang]

*IEEE Transactions on Systems, Man, and Cybernetics -- Part B: Cybernetics*


  Special Issue on

*New Advances in Video-based Gait Analysis and Applications: Challenges 
and Solutions***

 

The IEEE Transactions on Systems, Man, and Cybernetics -- Part B: 
Cybernetics is seeking original high-quality manuscripts for a Special 
Issue on New Advances in Video-based Gait Analysis and Applications, 
scheduled for publication in early 2010.

 

The study of human gait has generated much interest in the fields 
including biomechanics, clinical analysis, computer animation, robotics, 
and biometrics. In the early studies, traditional sensor-based obtrusive 
methods were commonly used. Recently, with the development of widespread 
availability of cameras and techniques of automated video analysis, 
video-based gait analysis has been one of most active but challenging 
research topics. As a relatively new biometric, gait can be used to 
signify the identification of individuals in image sequences. From a 
surveillance perspective, gait recognition is an attractive modality 
because it may be performed at a distance, surreptitiously. Gait motion 
capture and understanding are important in HCI and entertainment such as 
computer game and automation. Recently, gait has also been used for 
gender discrimination and age estimation, as well as traditional 
applications in medical diagnosis and rehabilitation.

  

There has been great progress made in the area of video-based gait 
analysis over the past few years, but not without limitations such as 
view dependence, simple and controlled environment, insufficient 
consideration of temporal influences on gait (such as clothes, carrying 
conditions, health states, body build variations due to weight), etc. 
This poses a number of significant challenges in video-based gait 
analysis and applications. More advanced solutions are thus needed to 
meet emerging application needs. As one major frontier for computer 
vision and pattern recognition research, statistical learning theories 
and techniques have been successfully applied for human tracking, motion 
modeling and recognition, which have evidenced rapid and fruitful 
developments, and are under the way to make further significant 
contributions to the area of vision-based gait analysis. To present and 
highlight the latest developments in vision-based gait analysis and 
applications in terms of both challenging areas and research approaches, 
this special issue is designed to aim at new advances in video-based 
gait analysis for different applications and will feature papers 
proposing new solutions to these real difficulties. We will solicit 
original contributions of researchers and practitioners from academia as 
well as industry, which address a wide range of theoretical and applied 
issues. Topics of interest include, but are not limited to:

 

o        Viewpoint invariant gait analysis from a single camera

o        Gait and scene of crime analysis

o        Invariant description of exploratory variables

o        Abnormal gait detection and analysis

o        Robust segmentation and tracking in complex scenes

o        Real time gait video analysis

o        Efficient storage, processing and retrieval of large amounts of 
video data

o        Gait classification and recognition

o        Gender and/or age classification from gait analysis

o        Gait-assisted diagnosis and/or treatment

o        Gait motion capture and performance evaluation

o        Gait biomechanics

o        Gait detection and tracking in videos

o        Gait feature fusion from camera networks

o        Semantic linkage between camera networks and other sensors

o        Gait databases

o        Other related aspects

 

The submitted articles must not have been previously published and must 
not be currently submitted for publication elsewhere. Prospective 
authors are responsible for understanding and adhering to the submission 
guidelines listed on 
http://www.ieeesmc.org/publications/Info_For_Authors_B.pdf. All 
submitted papers will be reviewed by at least three independent 
reviewers. Prospective authors should submit an electronic copy of their 
complete manuscript by the journal Manuscript Central 
http://mc.manuscriptcentral.com/smcb-ieee (Note that authors should 
select an issue-specific manuscript type from the drop-down menu of 
category:  Special Issue - Regular or Special Issue - Technical 
Correspondence, and then indicate in the comments to the editor box that 
the paper is meant for which special issue by entering the SI title 
there), according to the following timetable:

 

 

o        Full paper due: March 1, 2009

o        First notification: June 1, 2009

o        Revised manuscript due: August 1, 2009

o        Acceptance Notification: October 1, 2009

o        Final manuscript due: November 1, 2009

o        Publication of the special issue: 2nd quarter of 2010

* *

Please address all correspondence regarding this special issue to any of 
the following guest editors:

 

Liang Wang (wangliangnlpr at gmail.com), The University of Melbourne, Australia

Guoying Zhao (gyzhao at ee.oulu.fi), University of Oulu, Finland

Nasir Rajpoot (nasir at dcs.warwick.ac.uk), University of Warwick, UK

Mark Nixon (msn at ecs.soton.ac.uk), Southampton University, UK

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