Tutorial 1 - Mobile Computer Vision with OpenCV

Kirill Kornyakov, Sr SW Engineer at Itseez
Alexander Shishkov, Sr SW Engineer at Itseez

The market of personal electronic devices has changed dramatically over the last several years. Millions of smartphones and tablets are activated every day, these devices have large screens, powerful hardware and one or two cameras. Thus the public interest to image processing and computer vision on mobile devices is growing rapidly, and the technologies like Augmented Reality and Computational Photography are being actively researched and developed.

OpenCV is a free Open-source Computer Vision library, and it is one the popular tools of Computer Vision community with more than 6 million downloads to date. It is officially supported on Android and iOS, and many research and commercial applications are built on it. So, OpenCV is a free library with decent performance, and it could facilitate your R&D projects.

In this tutorial we will:

  • Highlight the current support of OpenCV on two major Mobile OS: iOS and Android.
  • Get familiar with basic principles of mobile development.
  • Learn how to run existing OpenCV code on a mobile device.
  • Get some pointers for future work, including sample projects and performance tips.

Target audience
Anybody, who has basic experience with OpenCV, and want to start with mobile/embedded development.


  • Kirill Kornyakov is a member of core OpenCV development team. He works at Itseez (Nizhny Novgorod, Russia), where he leads the development of the OpenCV library for Android operating system, with focus on performance optimization for NVIDIA Tegra platform. He also works on implementation of real-time computer vision algorithms, mainly Computational Photography applications. Kirill has B.Sc. and M.Sc. degrees from Nizhny Novgorod State University, Russia.

  • Alexander Shishkov is working in computer vision field for the last five years. He has developed technologies of video people counting systems, object detection and image retrieval systems. He created a continuous integration system for OpenCV and all OpenCV web resources. He also holds a MS in computational mathematics from Nizhny Novgorod State University.

Tutorial 2 - Visual Crowd Surveillance

Mubarak Shah, Computer Vision Lab, UCF

Tutorial Description
I will start with a brief overview of current Video Surveillance systems which follow the following steps: detection of moving objects, tracking of those objects from frame to frame, categorization of objects into different classes, and recognition of their behavior. Next, I will introduce visual analysis of crowded scenes and present our framework employing hydrodynamics approach. In particular, I will discuss solutions to three problems: Crowd flow Segmentation and Stability analysis, Tracking in High Density Crowd using Floor field models, and Identifying Behaviors in Crowded Scenes Through Stability Analysis for Dynamic Scenes. Finally, I will introduce Wide Area Surveillance problem, and present our approach for Many-Many Correspondence for Tracking of Swarms of Objects in Wide Area Aerial Videos. If time permits I will discuss our work on detecting motion patterns in crowded scenes.

Dr. Mubarak Shah, Agere Chair Professor of Computer Science, is the founding director of the Computer Visions Lab at UCF. He is a co-author of three books (Motion-Based Recognition (1997), Video Registration (2003), and Automated Multi-Camera Surveillance: Algorithms and Practice (2008)), all by Springer. He has published extensively on topics related to visual surveillance, tracking, human activity and action recognition, object detection and categorization, shape from shading, geo registration, photo realistic synthesis, visual crowd analysis, bio medical imaging, etc. Dr. Shah is a fellow of IEEE, IAPR, AAAS and SPIE. In 2006, he was awarded the Pegasus Professor award, the highest award at UCF, given to a faculty member who has made a significant impact on the university, has made an extraordinary contribution to the university community, and has demonstrated excellence in teaching, research and service. He is ACM Distinguished Speaker. He was an IEEE Distinguished Visitor speaker for 1997-2000, and received IEEE Outstanding Engineering Educator Award in 1997. He received the Harris Corporation's Engineering Achievement Award in 1999, the TOKTEN awards from UNDP in 1995, 1997, and 2000; Teaching Incentive Program awards in 1995 and 2003, Research Incentive Award in 2003 and 2009, Millionaires' Club awards in 2005, 2006, and 2009, University Distinguished Researcher award in 2007, SANA award in 2007, an honorable mention for the ICCV 2005 Where Am I? Challenge Problem, and was nominated for the best paper award in ACM Multimedia Conference in 2005. He is an editor of international book series on Video Computing; editor in chief of Machine Vision and Applications journal, and an associate editor of ACM Computing Surveys journal. He was an associate editor of the IEEE Transactions on PAMI, and a guest editor of the special issue of International Journal of Computer Vision on Video Computing. He was the program co-chair of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.

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