AISB convention 2017

  In the run up to AISB2017 convention, I've asked Joanna Bryson, from the organising team, to answer few questions about the convention and what comes with it. Mohammad Majid al-Rifaie (https://twitter.com/mohmaj) Tu...


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Harold Cohen

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Dancing with Pixies?...

At TEDx Tottenham, London Mark Bishop (the former chair of the Society) demonstrates that if the ongoing EU flagship science project - the 1.6 billion dollar "Human Brain Project” - ultimately succeeds in understanding all as...


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Computerised Minds. ...

A video sponsored by the society discusses Searle's Chinese Room Argument (CRA) and the heated debates surrounding it. In this video, which is accessible to the general public and those with interest in AI, Olly's Philosophy Tube ...


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Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...


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Notice

AISB miscellaneous Bulletin Item

CFP: IEEE TSMC-B special issue on video-based gait analysis and applications


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@gmail.com), The University of Melbourne, Australia

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

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

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