EURASIP Journal on Applied Signal Processing

  Special Issue on

  Visual Sensor Networks

  Call for Papers

Research into the design, development, and deployment of networked
sensing devices for high-level inference and surveillance of the
physical environment has grown tremendously in the last few years.

This trend has been motivated, in part, by recent technological
advances in electronics, communication networking, and signal
processing.

Sensor networks are commonly comprised of lightweight distributed
sensor nodes such as low-cost video cameras. There is inherent
redundancy in the number of nodes deployed and corresponding
networking topology. Operation of the network requires autonomous
peer-based collaboration amongst the nodes and intermediate
data-centric processing amongst local sensors. The intermediate
processing known as in-network processing is application-specific.
Often, the sensors are untethered so that they must communicate
wirelessly and be battery-powered. Initial focus was placed
on the design of sensor networks in which scalar phenomena
such as temperature, pressure, or humidity were measured.

It is envisioned that much societal use of sensor networks will
also be based on employing content-rich vision-based sensors.
The volume of data collected as well as the sophistication
of the necessary in-network stream content processing provide
a diverse set of challenges in comparison with generic scalar
sensor network research.

Applications that will be facilitated through the development
of visual sensor networking technology include automatic tracking,
monitoring and signaling of intruders within a physical area,
assisted living for the elderly or physically disabled, environmental
monitoring, and command and control of unmanned vehicles.

Many current video-based surveillance systems have centralized
architectures that collect all visual data at a central location
for storage or real-time interpretation by a human operator.
The use of distributed processing for automated event detection
would significantly alleviate mundane or time-critical activities
performed by human operators, and provide better network scalability.
Thus, it is expected that video surveillance solutions of the future
will successfully utilize visual sensor networking technologies.

Given that the field of visual sensor networking is still in its
infancy, it is critical that researchers from the diverse disciplines
including signal processing, communications, and electronics address
the many challenges of this emerging field. This special issue aims
to bring together a diverse set of research results that are essential
for the development of robust and practical visual sensor networks.

Topics of interest include (but are not limited to):

    o Sensor network architectures for high-bandwidth vision applications
    o Communication networking protocols specific to visual sensor networks
    o Scalability, reliability, and modeling issues of visual sensor networks
    o Distributed computer vision and aggregation algorithms for low-power
      surveillance applications
    o Fusion of information from visual and other modalities of sensors
    o Storage and retrieval of sensor information
    o Security issues for visual sensor networks
    o Visual sensor network testbed research
    o Novel applications of visual sensor networks
    o Design of visual sensors

Authors should follow the EURASIP JASP manuscript format
described at the journal site http://www.hindawi.info/asp/ .
Prospective authors should submit an electronic copy of their
complete manuscript through the EURASIP JASP's manuscript
tracking system at journal's web site, according
to the following timetable.

  Manuscript Due            December 1, 2005
  Acceptance Notification   April 1, 2006
  Final Manuscript Due      July 1, 2006
  Publication Date          3rd Quarter, 2006

GUEST EDITORS:

Deepa Kundur, Department of Electrical Engineering, Texas A&M University,
College Station, Texas, USA; deepa@ee.tamu.edu

Ching-Yung Lin, Distributed Computing Department, IBM TJ Watson Research
Center, New York, USA; chingyung@us.ibm.com

Chun Shien Lu, Institute of Information Science, Academia Sinica, Taipei,
Taiwan; lcs@iis.sinica.edu.tw