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                       CALL FOR PAPERS
   IEEE Transactions on Circuits and Systems for Video Technology
                      Special Issue on
          Video Analysis on Resource-Limited Systems
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Schedule
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Submission deadline:      **Dec. 15, 2010**
Notification of acceptance: Jun. 15, 2011
Final manuscript due:       Jun. 30, 2011
Tentative publication date: Oct. 2011


Guest Editors
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- Rama Chellappa, University of Maryland, USA
- Andrea Cavallaro, Queen Mary, University of London, UK
- Ying Wu, Northwestern University, USA	
- Caifeng Shan, Philips Research, The Netherlands
- Yun (Raymond) Fu, University at Buffalo (SUNY), USA
- Kari Pulli, Nokia Research Center (NRC) Palo Alto, USA


In many real-world video analytics systems, the available resources
are limited. This could mean low-quality data (e.g., limited imaging
resolution/sensor size/frame rate), such as video footage from
surveillance cameras and videos captured by consumers via mobile or
wearable cameras. Another dimension comes from limited amount of
processing power, for example, on mobile camera phones. There is a
huge demand for video analysis and computer vision techniques on
resource-limited systems. However, video analysis of low-quality
video data or on devices with limited computing power is still an
under-explored field. The existing video analysis research mainly
focuses on high-performance systems, that is, high-quality video data
or powerful computing platforms. There are many challenges when
addressing video analysis on resource-limited systems. For example,
How to effectively extract representative visual features from
low-quality data? How to fuse multiple low-resolution frames for
reliable recognition? How to accelerate vision algorithms for use on
mobile platforms? How to mitigate degrading factors caused by the
low-quality data? We have to adapt the existing approaches developed
for high-performance systems or find new techniques suitable for
resource-limited systems.

This special issue seeks to present and highlight the latest
developments on video analysis and computer vision on resource-limited
systems. Submissions that address real-world applications are especially
encouraged.

Topics of interest include, but are not limited to,
• Feature extraction from low-quality data
• Super-resolution
• Video stabilization
• Object detection in low-quality data
• Visual tracking on resource-limited systems
• Image recognition on mobile devices
• Face image analysis on resource-limited systems
• (Soft-)biometrics (face, body, gait, … ) in low-quality data
• Gesture recognition in low-quality data
• Human activity analysis in low-quality data
• Video analysis on resource-limited platforms (UAVs, toy robots,
  capsule endoscopy, …)
• Energy optimization for video coding on resource-limited devices
• Multiple-view analysis of low-quality data
• Video editing on mobile devices
• SLAM (simultaneous localization and mapping) on low-power devices
• Low-cost smart camera networks with embedded computing
• Video analysis on low-cost non-classical cameras (e.g., omni-directional
  cameras)
• Real-world applications on resource-limited systems (smart environments,
  safety and surveillance, entertainment …)
• Evaluation of video analysis algorithms on resource-limited systems