GlobalSIP 2016:

Symposium on Signal Processing for Understanding Crowd Dynamics

Schedule

Keynote Speaker

UCD-K1: Nuno Vasconcelos, University of California, San Diego

Understanding Video of Crowded Environments

Classical work in computer vision has emphasized the study of individual objects, e.g. object recognition or tracking. More recently, it has been realized that most of these approaches do not scale well to scenes that depict crowded environments. These are scenes with many objects, which are imaged at low resolution, and interact in complex ways. Solving vision problems in these environments requires the ability to model and reason about a crowd as a whole. I will review recent work in my lab in this area, including the design of statistical models for the appearance and dynamics of crowd video with multiple flows, and their application to the solution of problems such as crowd counting, dynamic background subtraction, anomaly detection, domain adaptation, and crowd activity analysis.

Organizing Committee

• Lucio Marcenaro University of Genova, Italy

Technical Program Chairs

• Nicola Conci, University of Trento, Italy
• Peter Tu, GE Global Research, USA

[Download the PDF Call for Papers]

The Symposium on Signal Processing for Understanding Crowd Dynamics will focus on the signal processing challenges in analyzing potentially crowded environments. This Symposium addresses timely and challenging problems on realizing automatic ambient intelligent systems that are able to deal with crowds from the signal processing perspective. Standard signal processing approaches are typically not suited to this kind of challenging environments and there is often the need of specific methodologies and tools.

The symposium aims to bring together researchers, practitioners and students from signal processing and surveillance-related fields to share knowledge on methodologies, features and results related to the evaluation, modeling and understanding of crowded environments.

This symposium focuses on underlying theory, methods, systems, and applications of crowd analysis and understanding and invites submissions in areas listed below.

Submissions are welcome on topics including:

• Video analytics algorithms
• Cognitive dynamic systems
• Bio-inspired techniques
• Simulation tools
• Heterogeneous systems for signal processing
• Interaction modeling
• Crowd emotion sensing
• Crowd behavior modeling
• Graph signal processing
• Deep learning
• Big data analysis
• Convolutional neural networks
• Compressive sensing

Paper Submission

Prospective authors are invited to submit full-length papers, with up to five pages for technical content including figures and possible references, and with one additional optional 6th page containing only references. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Submission is through the GlobalSIP website at http://2016.ieeeglobalsip.org/Papers.asp.

More Information

For more details, see http://www.sp-crowd.com/.