Volume 26 | Issue 11

IEEE Transactions on Circuits and Systems for Video Technology covers all aspects of visual information relating to video or that have the potential to impact future developments in the field of video technology and video systems, including but not limited to:

  1. (a) image/video processing: acquisition, representation, display, processing, transform, filtering, enhancement, restoration, watermarking;
  2. (b) image/video analysis and computer vision: characterization, classification, detection, tracking, assessment, segmentation, summarization, understanding, motion estimation, feature extraction, machine learning, machine intelligence, pattern analysis, pattern recognition, neural networks;
  3. (c) image/video compression: quantization, compression, quality assessment, rate control, error resilience, multiview, standards;
  4. (d) image/video communication: coding, streaming, distribution, interaction, networking, transport, wireless and mobile systems;
  5. (e) image/video storage: archives, networks, content management, databases, indexing, search, retrieval;
  6. (f) image/video hardware/software systems: architecture, hardware, software, multiprocessors, parallel processors, algorithms, VLSI, circuits, high-speed, real-time, low-power systems;
  7. (g) image/video applications: synthetic imaging, augmented imaging, video gaming, virtual reality, audio-visual systems, human-computer interaction, multimedia systems, multi-camera systems, surveillance, security, forensics, medical imaging, big data systems, cloud computing, and other video-related technologies.

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Dan Schonfeld
Editor in Chief - 2016 - 2017
ECE Dept. (M/C 154)
University of Illinois at Chicago (UIC)
851 S. Morgan Street – 1020 SEO
Chicago, Illinois

Dr. Shipeng Li
Deputy Editor-in-Chief
Microsoft Research Asia


Presents the table of contents for this issue of the publication.

Provides a listing of the editorial board, current staff, committee members and society officers.

Despite significant progress in human behavior analysis over the past few years, most of today’s state-of-the-art algorithms focus on analyzing individual behavior in a simple environment monitored by a single camera. Recently, the widespread availability of cameras and a growing need for public safety have shifted the attention of researchers in video surveillance from individual... Read more on IEEE Xplore

In advanced video surveillance systems, people localization is usually a part of the complete system and should be accomplished in a short time so as to reserve sufficient processing time for subsequent high-level analysis, such as abnormal event/behavior detection and intruder detection. Hence, in addition to localization accuracy, computational efficiency is of critical importance as well. In... Read more on IEEE Xplore

Most existing tracking approaches are based on either the tracking by detection framework or the tracking by matching framework. The former needs to learn a discriminative classifier using positive and negative samples, which will cause tracking drift due to unreliable samples. The latter usually performs tracking by matching local interest points between a target candidate and the tracked target... Read more on IEEE Xplore