Content Gazette - February 2014 - 39

Call for Papers
Journal of Selected Topics in Signal Processing
Special Issue on
Signal Processing for Situational Awareness from
Networked Sensors and Social Media
Situational awareness is of great interest in security/surveillance, disaster management, environmental monitoring, etc.
At the same time, distributed data sources are common today and generate a wealth of information, e.g., surveillance
cameras, smartphones, parking occupancy sensors, RFID (proximity) sensors. However, there exists a gap between the
wealth of distributed information captured and the understanding of a scene where the sensors are located. The goal of this
special issue is an attempt at bridging this gap by bringing together various signal processing methodologies associated
with such data analysis. Since situational awareness methods in practice today often combine sensor measurements with
information gleaned from social media, this issue will consider both these information sources.
Challenges in information processing from large sensor networks are many - from the use of single sensors adapting
internal or external parameters, to the cooperation of multiple sensors in a networked manner. Also, the amount of data that
needs to be analyzed can be prohibitive, leading to various "big data" challenges. These challenges are particularly acute
for video data, the main surveillance modality today, due to its sheer volume. Recent technological developments have also
led to more efficient and robust sensors that more tightly couple the acquisition and analysis phases (e.g., network cameras,
smartphones). This requires the development of algorithms, ideally implemented close to the sensor and which are
specifically tuned to the characteristics of the sensors. Seeking solutions to the above challenges cannot be done without
considering the usage of resources, such as energy consumption, communication bandwidth, computational power, etc.
Finally, a very recent data modality, that is likely to play a significant role in the future, comes from social media in the
form of text, images, videos, and sound recordings. The fusion of social media data with traditional surveillance streams is
an unchartered, but potentially fertile, territory.
This special issue proposal is innovative because it aims to bring together, in one publication, novel research from
diverse areas of signal processing with the common goal of exploiting "high volume data" collected daily for more efficient
situational awareness. We will encourage submissions describing different approaches, both in terms of the number of
sensors (networked vs. single), their types (network cameras, smart phones, radar, social media, etc.), data processing
methodologies, and application domains. The fusion of data captured by different sensors or different platforms will be of
great interest for the proposed issue as well. In order to clearly differentiate this issue from others in JSTSP, papers
submitted must have a significant contribution to advancing the state of the art in situational awareness. Work with a
variety of sensor modalities is welcome, including novel multi-modal fusion techniques.
A list of topics follows, but we will encourage additional topics falling within the purview of situational awareness.
 Sensors: Novel sensors, Sensing from mobile platforms (UAV, UGV, satellite, etc.), Beyond visual perception sensing
(radar, hyperspectral, etc.)
 Sensor networks: Sensor network processing and control, Distributed detection, localization and tracking, Distributed
machine learning for scene analysis, Multiagent coordination for wide-area coverage and analysis, Re-identification and
network tracking, Network resource management, Information fusion over distributed sensor networks
 System-level scene understanding: Multi-modal fusion, Context-based object description and scene understanding,
Event annotation, summarization and visualization, Inferring spatio-temporal, causal and contextual relations between
events, Multimedia Analytics
 Exploitation of social media for situational awareness: Visual data analysis in large online repositories (e.g.,
YouTube, Instagram), Context analysis in social media (e.g., Twitter, Facebook, etc.), Fusion of sensor and social data
Prospective authors should visit http://www.signalprocessingsociety.org/publications/periodicals/jstsp/ for information on
paper submission. Manuscripts should be submitted using Manuscript Central at http://mc.manuscriptcentral.com/jstsp-ieee.
Dates

Paper Submission

1 March 2014

First Review

1 June2014

Revision Due

1 August 2014

Final Decision

1 October 2014

Camera Ready

15 November 2014

Guest Editors
Amit K. Roy-Chowdhury, University of California, Riverside, USA; amitrc@ee.ucr.edu
Christian Micheloni, Università degli Studi di Udine, Italy; christian.micheloni@uniud.it
Janusz Konrad, Boston University, USA; jkonrad@bu.edu
Mohan S. Kankanhalli, National University of Singapore, Singapore; mohan@comp.nus.edu.sg
Pramod Varshney, Syracuse University, USA; varshney@syr.edu

www.signalprocessingsociety.org

[39]

FEBRUARY 2014

Expected Publication

First half of 2015
http://www.signalprocessingsociety.org/publications/periodicals/jstsp/ http://mc.manuscriptcentral.com/jstsp-ieee http://www.signalprocessingsociety.org
Table of Contents for the Digital Edition of Content Gazette - February 2014
