CS Other Presentations
Besides Colloquiums, the Department of Computer Science at the University of Cyprus also holds Other Presentations (Research Seminars, PhD Defenses, Short Term Courses, Demonstrations, etc.). These presentations are given by scientists who aim to present preliminary results of their research work and/or other technical material. Other Presentations serve as a forum for educating Computer Science students and related announcements are disseminated to the Department of Computer Science (i.e., the csall list):RSS Directions
Presentations Coordinator: Demetris Zeinalipour
PhD Defense: Data-Driven Techniques for Virtual Crowds, Mr. Panayiotis Charalambous (University of Cyprus, Cyprus), Monday, December 16, 2013, 10:00-11:00 EET.
The Department of Computer Science at the University of Cyprus cordially invites you to the PhD Defense entitled:
Data-Driven Techniques for Virtual Crowds
Speaker: Mr. Panayiotis Charalambous
Affiliation: University of Cyprus, Cyprus
Category: PhD Defense
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Monday, December 16, 2013
Time: 10:00-11:00 EET
Host: Yiorgos Chrysanthou (yiorgos-AT-cs.ucy.ac.cy)
Virtual crowds are important in a variety of applications such as computer games, movies, training simulations and safety modelling. Increasing processing power enables designers and programmers to add multitudes of realistic looking virtual characters in real-time applications. Despite these advances, there is a significant gap between rendered appearance and simulated behaviour of crowds. This thesis is addressing some of the shortcomings of data driven techniques for simulating and evaluating crowd behaviours. Firstly, the Perception Action Graph (PAG) framework is proposed for efficient data-driven crowd simulation. By employing this framework and using as input data from videos of real world crowds, fast, consistent and believable steering behaviours for virtual human crowds can be generated. Secondly, we propose a multi-objective data-driven framework for crowd evaluation based on Pareto Depth Analysis. This method employs recent methods in Machine Learning for novelty/outlier detection under multiple criteria. Using as input well behaved crowds, the proposed framework identifies abnormal parts of the simulation and pinpoints them for further examination. Finally, on the belief that a higher level understanding of crowd behaviours will take us towards better crowd simulation, evaluation and authoring, a method that annotates pedestrian trajectory segments into higher level descriptors is presented. The method uses both local and global knowledge of crowd trajectories and successfully identifies behaviours such as wandering around and group formations.
Panayiotis Charalambous is a PhD candidate at the Department of Computer Science of the University of Cyprus under the supervision of Dr. Yiorgos Chrysanthou. He completed his Undergraduate studies at the Department of Informatics and Telecommunications of the University of Athens, Greece in 2002 and his Graduate studies at the same department in 2005 specializing in “Computing Systems Technology”. He worked as a Research scientist at the Xi Computer Architecture Lab of the University of Cyprus under Dr. Yiannakis Sazeides focusing on power and temperature models for general purpose CPUs. He is a member of the Graphics Lab of the University of Cyprus since 2007, where we worked on a number of projects as a researcher and developer. His research interests include crowd simulation and evaluation, real-time simulation models, dynamic spatial data structures, GPU architectures and power aware computing.
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