Special Issue on Video Analytics: Challenges, Algorithms, and Applications Call for Papers

Call For Papers
IEEE Transactions on Multimedia
Special Issue on Video Analytics: Challenges, Algorithms, and Applications

Video analytics, also known as video content analysis, refers to the
capability of automatically analyzing video to extract
knowledge/information and detect and determine temporal and spatial
events. Video analytics is still an emerging technology with
techniques that are continuously being developed to help make
widespread implementation feasible in the years ahead. Such analytics
has been typically used in semantic categorization and retrieval of
video databases. A goal of this special issue is to focus on the real
time systems aspect of video analytics beyond categorization and
retrieval.

With increasing hardware capability and advances in algorithms used,
real-time video analytics is now being used in a wide range of domains
including entertainment,health-care, retail, automotive, transport,
home automation, emotion analysis, aesthetics, inappropriate content
detection, safety and security.From the sensing aspect, 3D cameras
such as RGB-D and LiDAR (Light Detection and Ranging) cameras are
becoming more and more affordable, enabling additional areas of
research and applications, such as, self-driving cars employing video
analytics on LiDAR captured data for path planning as well as obstacle
detection. Research advances in hardware has facilitated
miniaturization of components needed for image sensing, processing,
communication and rendering. This miniaturization has also led to
Internet of Things (IoT) devices and solutions with visual information
processing at the core. Since video analytics on wearable/IoT/mobile
devices need to work with small computational resources on-board,
distributed algorithms are being developed to have these devices work
in tandem with servers in cloud and high performance computing
clusters.

This special issue aims to provide the much needed research forum for
sharing the challenges and recent advances in video analytics
algorithms and applications. We envisage that this forum will bring
together researchers working on new approaches in multiple, related
fields: camera (both 2D and 3D) pipeline processing, machine learning,
video content analysis, wearable/mobile devices, and application
domains.

The topics of interest to this special issue include, but not limited
to:

Systems for Real-time Video Analytics Including: (a) 2D and 3D Camera
pipeline processing strategies; (b) GPU as well as specialized
hardware based acceleration techniques; (c) Large scale analytics on
the Cloud and High Performance Computing Clusters; (d) Analytics
on/with/using mobile and wearable devices for real-time feedback.

Novel Algorithms for Real-time Video Analytics Including:

(a) Efficient Deep Learning Models Addressing High Video Analytics
Complexity; (b) Distributed Algorithms for Analyzing Videos over
Large-Scale Camera Networks or Client-Server Systems; (c) Algorithms
Addressing Complexity, Storage, and Power Constraints of Large-Scale
Video Analytics.

Application Domains: (a) Entertainment, health-care, retail,
automotive, transport, home automation, egocentric video, safety and
security; (b) New benchmark datasets supporting real-time video
analytics-based applications.

Important Dates

Paper submission due: April 15, 2017; Revision Due: August 15, 2017;
Final manuscript due: December 1, 2017;

Guest Editors:

First-round review completed: July 1, 2017 Second-round review
completed: November 1, 2017 Publication date: Early-2018

Balakrishnan Prabhakaran, University of Texas at Dallas; Yu-Gang
Jiang, Fudan University Hari Kalva, Florida Atlantic University;
Shih-Fu Chang, Columbia University 

Submission Procedure:
http://mc.manuscriptcentral.com/tmm-ieee