Connectionists: CVNet - [journal] Signal, Image and Video Processing Special issue on "Semantic representations for social behavior analysis in video surveillance systems"

[Shengping Zhang]

Dear All,

Please find below the call for papers for a special issue of Signal, Image and Video Processing  on “Semantic representations for social behavior analysis in video surveillance systems”. Apologies for cross-posting.

Signal, Image and Video Processing
Special issue

Semantic representations for social behavior analysis in video surveillance systems

Call for Papers

Video surveillance has been attracting increasing attentions in the computer vision community because of its wide industrial applications and important scientific values. Among the related topics, automatic behavior analysis plays an extremely important role and has witnessed tremendous progress in the last twenty years. Recently, researchers in video surveillance shift their attention from the monitoring of a single person’s behaviours in a relatively simple environment to that of social behavior of multiple persons in crowded environments. In contrast to single person’s behavior, social behavior analysis faces more challenges such as complex interaction, diverse semantics and various expressions. This is due to the gap between the information directly extracted from videos and semantic interpretations by our human beings.

To bridge this gap, a number of feature representation approaches (e.g. Cuboids, HOG/HOF, HOG3D and eSURF) have been subsequently reported to address the coherence between the extracted features and the semantic interpretations. Unfortunately, due to the redundancy and complexity, these hard-crafted features may lead to diverse variations of semantic representations for social behavior analysis.

In recent years, novel semantic representations have proven to be an effective tool for social behavior analysis. For example, social force model and its variant have proven to perform well in social behavior recognition. Such high-level semantic representations achieve desired performance even if in crowded environments. Besides, statistical approaches, syntactic approaches, and description-based approaches also gain increasing attention in computer vision community.

The primary purpose of this special issue is to organize a collection of recently developed high-level semantic representations for social behavior analysis, spreading over motion trajectory acquisition and analysis, semantic feature extraction, social behavior analysis and applications. The special issue is intended to be an international forum for researchers to report the recent developments in this field in an original research paper style. The topics include, but are not limited to:

· Real-time moving object detection and tracking in crowded environments;

· Face detection and recognition in crowded environments

· 3D scene reconstruction and occlusion handling;

· Long-term trajectory clustering and analysis for social behaviors;

· Probabilistic statistical models for local semantic representation;

· Context model for global semantic representation;

· Event recognition in crowded environments;

· Abnormal behavior detection in crowded environments;

· Real-time algorithms for large scale social behavior analysis; 

Schedule (tentative)

Deadline for manuscript submission: December 31, 2013

Notification of acceptance: April 15, 2014

Complete Publication Materials Due: July 15, 2014

Publication date: 2015

Submission Guidelines

Prospective authors should prepare their manuscripts according to the Signal, Image and Video Processing guidelines (http://www.springer.com/engineering/signals/journal/11760). Manuscripts should be submitted via http://www.editorialmanager.com/sivp/ with article type chosen as “S.I.: Semantic representations for social behavior analysis”. Manuscripts should be self-contained and not exceed 30 double spaced pages typed in 10 points or larger. All submissions will be peer reviewed for originality, technical content and relevance to the theme of the special issue.

Guest Editors:

Shengping Zhang, Harbin Institute of Technology, China, Email: s.zhang at hit.edu.cn

Huiyu Zhou, Queen’s University Belfast, United Kingdom, Email: h.zhou at ecit.qub.ac.uk

Baochang Zhang, Beihang University, China, Email: bczhang at buaa.edu.cn

Zhenjun Han, University of Chinese Academy of Sciences, China, Email: hanzhj at ucas.ac.cn

Best regards,

-- 
Dr. Shengping Zhang




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