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CENTRE OF RESEARCH EXCELLENCE FOR ADVANCED COOPERATIVE SYSTEMS

The Centre of Research Excellence for Advanced Cooperative Systems (ACROSS) is an interdepartmental research centre at the University of Zagreb Faculty of Electrical Engineering and Computing. The centre performs research in cooperative systems related to robotics, networked embedded systems and renewable energy systems. Its establishment and operation is funded by the European FP-7 Capacities "Research Potential" program [285939, FP7-REGPOT-2011-1].


Published: 2013-06-28 at 20:35
Ph.D. thesis defense of ACROSS...

The Council of the Faculty of Electrical Engineering and Computing in Zagreb, on its 627th session, held on April 17, 2013, unanimously accepted the evaluation of Ph.D. thesis of Karla Brkić, dipl.ing. as proposed by the Thesis Evaluation Committee. The Faculty Council nominated members of the Ph.D. thesis Defence Committee as follows:

  1. Professor Sven Lončarić, Ph.D.
  2. Professor Siniša Šegvić, Ph.D.
  3. Professor Hrvoje Gold, Ph.D., University of Zagreb, Faculty of Transport and Traffic Sciences

and their deputy:

  1. Assistant Professor Tomislav Hrkać, Ph.D.

Advisors:  Professor Zoran Kalafatić, Ph.D. and Ao. Univ.-Prof. Dipl.-Ing. Dr. Techn. Axel Pinz, Graz University of Technology, Austria.

 

Karla Brkić, dipl.ing. will defend her Ph.D. thesis entitled:

"Structural analysis of video by histogram-based description of local space-time appearance"
on Tuesday, July 2, 2013 at 11:30 AM
at the Department of Electronics, Microelectronics, Computer and Intelligent Systems

(Building D – III floor)

 

More about the thesis and the speaker can be found in the detailed news content.

Abstract:

The methods for representation, classification and reasoning about video data are actively researched in the computer vision community, given a large number of interesting applications such as human action recognition, video segmentation, event detection, gesture recognition, and dynamic texture recognition. The goal of this thesis is to investigate the methods for video analysis that are generally applicable to any kind of video data, regardless of the phenomenon represented by the data. Special emphasis is placed on the analysis of videos in an online scenario, where not all frames of a video are available in advance. The thesis introduces the notion of a spatio-temporal structure as a basic unit of video information. A method for representing spatio-temporal structures as grids of histogram is proposed, and the derived grid-of-histograms representation is used to build two different kinds of descriptors: the spatio-temporal appearance (STA) descriptors and the COIN descriptors. A detailed experimental evaluation is provided, illustrating the suitability of STA descriptors as feature vectors in the problems of traffic sign recognition, human action recognition and dynamic texture recognition, and the suitability of COIN descriptors in determining the structural properties of the 3D world.

 

CV:

Karla Brkić received her M. Eng. (dipl. ing.) degree in Computing from the Faculty of Electrical Engineering and Computing in September 2007. Since 2008, she has been employed at the same Faculty, as a research associate at the Department of Electronics, Microelectronics, Computer and Intelligent Systems, where she works towards a PhD degree. From 2008 – 2012 she participated in various research projects, including a project funded by the Croatian Science Foundation, a bilateral Croatian-Austrian research project and a research project funded by the University of Zagreb Development Fund. In her research she has been extensively collaborating with the Vision-based Measurement Group of the Graz University of Technology, Austria. Since September 2012, she participates in the ACROSS project, where she is a member of the Applied Cognition and Vision Group. She has co-authored four journal papers and seven papers published in the proceedings of international conferences. Her research interests include representation, classification and reasoning about video data in computer vision.

Mario Bukal
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FUNDING
 

ACROSS project has received research funding from the Seventh Framework Programme of the European Union (Grant Agreement No. 285939 FP7-REGPOT-2011-1).


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