IET Computer Vision – Special Issue: Video Analytics

Hi all,

This is to inform all of you of the call for papers for the Special Issue on Video Analytics in the IET Computer Vision journal where I am participating as Guest Editor:

Important dates
Submission deadline: 1 Jul 2015
Publication date: Apr 2016

IET Computer Vision


Text of the call:
IET Computer Vision
Special Issue: Video Analytics

As digital technologies advance, video has become ubiquitous and hence a rich source of information. Video analytics (or video content analysis) is an important area of computer vision which is concerned with the process of making sense of video content in order to ultimately understand video. Video analytics appears in different forms, such as activity recognition, motion detection, object detection and recognition, person detection and recognition, event and scenario recognition, anomaly detection, and identity recognition and verifi cation. Video analytics can be applied in a wide range of domains including healthcare, retail, transport, smart homes, safety and security. Aims and objectives: The aims of the Special Issue are to raise the awareness of the importance of video analytics, to showcase the state of the art in video analytics, and to provide an opportunity to accelerate the advancement of video analytics. Specifi c objectives are (1) reporting the latest developments in video analytics (2) identifying major research challenges in a general framework of video analytics (3) and providing visions for the advancement of the state of the art. The Special Issue is expected to offer a mixture of invited papers and contributed papers, along with an editorial. Prospective authors are invited to submit unpublished, original work to this Special Issue to be peer-reviewed for publication. The submitted papers should address scientifi c challenges in video analytics including but not limited to the following topics:

  • image/video representation
  • feature extraction
  • interest modelling
  • formulation of the problem (e.g., as one-class or two-class machine learning, probabilistic/deep learning, or invariant image comparison)
  • relevant fundamental problems (e.g., similarity, invariance)

The submitted papers may also present novel solutions or report new applications.

All submissions are subject to the journal’s peer-review procedures. The authors should follow the journal’s Author Guide at when preparing papers for submission to the Special Issue.

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