Publications

Virtual Environment Navigation Assisted by Neural Networks.
Georgios Kyrlitsias, Amyr Borges Fortes Neto, Panayiotis Charalambous, Marios Avraamides and Yiorgos Chrysanthou. (2018).
Virtual Humans and Crowds for Immersive Environments (VHCIE '18).

Applications using Virtual Environments (VE) are becoming increasingly popular due to greater computational capacity and improvements in graphics processing units and tracking devices. As a result, much research has been carried out on various aspects of VEs, including the input devices that can be used to navigate scenes when physical movement is not permitted. Here, we test whether implementing a neural network to assist users avoid collisions with virtual obstacles, can benefit the navigation experience. Our hypothesis was that users with no gaming experience in particular, would appreciate the assistance of the neural network in navigation. However, our pilot data suggest the exact opposite: participants with video game experience liked the assisted navigation more than participants with no video game experience.

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Simulating Heterogeneous Crowds with Interactive Behaviors.
Edited by: Nuria Pelechano, Jan M. Allbeck, Mubbasir Kapadia, Norman I. Badler. CRC Press (2016)

I had the privilege of co-authoring two book chapters with Yiorgos Chrysanthou on Data-Driven Crowd simulation and evaluation. More specifically, we wrote Chapter 3:
Learning Heterogeneous Crowd Behavior from the Real World and Chapter 10:
Data-Driven Crowd Evaluation.
Book Website

Group Modeling: A Unified Velocity-Based Approach.

Ren Z., Charalambous P., Bruneau J., Peng Q. and Pettre J. (2016). Computer Graphics Forum.
Presented at Eurographics 2017.

Crowd simulators are commonly used to populate movie or game scenes in the entertainment industry. Even though it is crucial to consider the presence of groups for the believability of a virtual crowd, most crowd simulations only take into account individual characters or a limited set of group behaviors. We introduce a unified solution that allows for simulations of crowds that have diverse group properties such as social groups, marches, tourists and guides, etc. We extend the Velocity Obstacle approach for agent based crowd simulations by introducing Velocity Connection; the set of velocities that keep agents moving together whilst avoiding collisions and achieving goals. We demonstrate our approach to be robust, controllable, and able to cover a large set of group behaviors.

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Crowd Art: Density and Flow Based Crowd Motion Design.

Jordao K., Charalambous P., Christie M., Pettre J. and P. Cani, Marie (2015). Motion in Games 2015

Artists, animation and game designers are in demand for solutions to easily populate large virtual environments with crowds that satisfy desired visual features. This paper presents a method to intuitively populate virtual environments by specifying two key features: localized density, being the amount of agents per unit of surface, and localized flow, being the direction in which agents move through a unit of surface. The technique we propose is also time-independant, meaning that whatever the time in the animation, the resulting crowd satisfies both features. To achieve this, our approach relies on the Crowd Patches model. After discretizing the environment into regular patches and creating a graph that links these patches, an iterative optimization process computes the local changes to apply on each patch (increasing/reducing the number of agents in each patch, updating the directions of agents in the patch) in order to satisfy overall density and flow constraints. A specific stage is then introduced after each iteration to avoid the creation of local loops by using a global pathfinding process. As a result, the method has the capacity of generating large realistic crowds in minutes that endlessly satisfy both user specified densities and flow directions, and is robust to contradictory inputs. At last, to ease the design the method is implemented in an artist-driven tool through a painting interface.

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Video Paper (ACM) Project Publication Page

Emotion Analysis and Classification: Understanding the Performers' Emotions Using the LMA Entities.

Aristidou, A., Charalambous, P. and Chrysanthou, Y. (2015) Computer Graphics Forum. Presented at Eurographics 2016.

The increasing availability of large motion databases, in addition to advancements in motion synthesis, has made motion indexing and classification essential for better motion composition. However, in order to achieve good connectivity in motion graphs, it is important to understand human behaviour; human movement though is complex and difficult to completely describe. In this paper, we investigate the similarities between various emotional states with regards to the arousal and valence of the Russell's circumplex model. We use a variety of features that encode, in addition to the raw geometry, stylistic characteristics of motion based on Laban Movement Analysis (LMA). Motion capture data from acted dance performances were used for training and classification purposes. The experimental results show that the proposed features can partially extract the LMA components, providing a representative space for indexing and classification of dance movements with regards to the emotion. This work contributes to the understanding of human behaviour and actions, providing insights on how people express emotional states using their body, while the proposed features can be used as complement to the standard motion similarity, synthesis and classification methods.

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Folk Dance Evaluation Using Laban Movement Analysis.

Andreas Aristidou, Efstathios Stavrakis, Panayiotis Charalambous, Yiorgos Chrysanthou, and Stephania Loizidou Himona. ACM Journal on Computing and Cultural Heritage. Vol. 8, Issue 4, Article 20 (August 2015).

Motion capture (mocap) technology is an efficient method for digitizing art performances, and is becoming increasingly popular in the preservation and dissemination of dance performances. Although technically the captured data can be of very high quality, dancing allows stylistic variations and improvisations that cannot be easily identified. The majority of motion analysis algorithms are based on ad-hoc quantitative metrics, thus do not usually provide insights on style qualities of a performance. In this work, we present a framework based on the principles of Laban Movement Analysis (LMA) that aims to identify style qualities in dance motions. The proposed algorithm uses a feature space that aims to capture the four LMA components (Body, Effort, Shape, Space), and can be subsequently used for motion comparison and evaluation. We have designed and implemented a prototype virtual reality simulator for teaching folk dances in which users can preview dance segments performed by a 3D avatar and repeat them. The user’s movements are captured and compared to the folk dance template motions; then, intuitive feedback is provided to the user based on the LMA components. The results demonstrate the effectiveness of our system, opening new horizons for automatic motion and dance evaluation processes.
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The PAG Crowd: A Graph Based Approach for Efficient Data‐Driven Crowd Simulation.

Charalambous Panayiotis and Chrysanthou Yiorgos. In Computer Graphics Forum, vol. 33, no. 8, pp. 95-108. 2014.

We present a data‐driven method for the real‐time synthesis of believable steering behaviours for virtual crowds. The proposed method interlinks the input examples into a structure we call the perception‐action graph (PAG) which can be used at run‐time to efficiently synthesize believable virtual crowds. A virtual character's state is encoded using a temporal representation, the Temporal Perception Pattern (TPP). The graph nodes store groups of similar TPPs whereas edges connecting the nodes store actions (trajectories) that were partially responsible for the transformation between the TPPs. The proposed method is being tested on various scenarios using different input data and compared against a nearest neighbours approach which is commonly employed in other data‐driven crowd simulation systems. The results show up to an order of magnitude speed‐up with similar or better simulation quality.
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A Data‐Driven Framework for Visual Crowd Analysis.

Panayiotis Charalambous, Ioannis Karamouzas, Stephen J. Guy, and Yiorgos Chrysanthou. 2014. A Data-Driven Framework for Visual Crowd Analysis. Comput. Graph. Forum 33, 7 (October 2014), 41-50. DOI=10.1111/cgf.12472 http://dx.doi.org/10.1111/cgf.12472

We present a novel approach for analyzing the quality of multi-agent crowd simulation algorithms. Our approach is data-driven, taking as input a set of user-defined metrics and reference training data, either synthetic or from video footage of real crowds. Given a simulation, we formulate the crowd analysis problem as an anomaly detection problem and exploit state-of-the-art outlier detection algorithms to address it. To that end, we introduce a new framework for the visual analysis of crowd simulations. Our framework allows us to capture potentially erroneous behaviors on a per-agent basis either by automatically detecting outliers based on individual evaluation metrics or by accounting for multiple evaluation criteria in a principled fashion using Principle Component Analysis and the notion of Pareto Optimality. We discuss optimizations necessary to allow real-time performance on large datasets and demonstrate the applicability of our framework through the analysis of simulations created by several widely-used methods, including a simulation from a commercial game.
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Optimization-based computation of locomotion trajectories for crowd patches

Jose Guillermo Rangel Ramirez, Devin Lange, Panayiotis Charalambous, Claudia Esteves, and Julien Pettré. 2014. Optimization-based computation of locomotion trajectories for crowd patches. In Proceedings of the Seventh International Conference on Motion in Games (MIG '14). ACM, New York, NY, USA, 7-16. DOI: https://doi.org/10.1145/2668064.2668094

Over the past few years, simulating crowds in virtual environments has become an important tool to give life to virtual scenes; be it movies, games, training applications, etc. An important part of crowd simulation is the way that people move from one place to another. This paper concentrates on improving the crowd patches approach proposed by Yersin et al. [Yersin et al. 2009] that aims on efficiently animating ambient crowds in a scene. This method is based on the construction of animation blocks (called patches) concatenated together under some constraints to create larger and richer animations with limited run-time cost. Specifically, an optimization based approach to generate smooth collision free trajectories for crowd patches is proposed. The contributions of this work to the crowd patches framework are threefold; firstly a method to match the end points of trajectories based on the Gale-Shapley algorithm [Gale and Shapley 1962] is proposed that takes into account preferred velocities and space coverage, secondly an improved algorithm for collision avoidance is proposed that gives natural appearance to trajectories and finally a cubic spline approach is used to smooth out generated trajectories. We demonstrate several examples of patches and how they were improved by the proposed method, some limitations and directions for future improvements.
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Reconstruction of everyday life in 19th century nicosia

Panayiotis Charalambous, Hesperia Iliadou, Charalambos Apostolou, and Yiorgos Chrysanthou. 2012. Reconstruction of everyday life in 19th century nicosia. In Proceedings of the 4th international conference on Progress in Cultural Heritage Preservation (EuroMed'12), Marinos Ioannides, Dieter Fritsch, Johanna Leissner, Rob Davies, and Fabio Remondino (Eds.). Springer-Verlag, Berlin, Heidelberg, 568-577. DOI=http://dx.doi.org/10.1007/978-3-642-34234-9_58

This paper presents the first stages of a larger project concerning the study and realization of a 3D interactive environment of everyday life in 19th century Nicosia. The presented study involves the recreation of the built urban environment (i.e. the architecture of the city) based on historic and archival information taken from the first Land Registry documentations taking place on the island at the end of the Ottoman era by British engineers.
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Reviving Nicosia of the XIXth Century

Hesperia Iliadou, Panayiotis Charalambous and Yiorgos Chrysanthou. 2012. EAUH 2012, Prague, Czech Republic.

In this paper we describe our on-going work on the virtual reconstruction and population of XIXth Century Nicosia. The project involves the development of a semi-automatic pipeline that will take as input maps and land-registry deeds and will give as a result a 3D model of the urban space inhabited by animated virtual characters, guided by the historic information. The aim is to present a unique insight to the everyday life of a bygone era. In the city, now divided by a wall into Muslim north and Christian south, a population of Muslims coexisted with the Christian-Orthodox population as well as with other minorities, in an interesting intertwine of culture and religion located in the dense built environment within the city walls.
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Design, implementation and first results of a 3RD generation digital photogrammetric system from trunk surface assessment and scoliosis screening.

Grivas, T. B., P. Patias, K. Soultanis, E. Stylianidis, V. Tsioukas, Ch Georgiadis, C. Andreou, P. Charalambous, and Y. Chrysanthou. Scoliosis 7, no. Suppl 1 (2012): P14.

Scoliosis patients typically undergo numerous spinal radiographs and exposed to relatively high doses of ionizing radiation. This has raised concern regarding the effects of this repeated exposure. Additionally assessment of spinal deformities using surface topography of the back is currently considered essential. Digital Photogrammetry can contribute in non-invasive measurements of the patient’s back and 3D reconstruction of surface shape from digital photos.

Learning Crowd Steering Behaviors from Examples.

Panayiotis Charalambous and Yiorgos Chrysanthou. Motion in Games. Springer Berlin Heidelberg, 2010. 35-35.

Crowd steering algorithms generally use empirically selected stimuli to determine when and how an agent should react. These stimuli consist of information from the environment that potentially influence behavior such as an agent’s visual perception, its neighboring agents state and actions, locations of nearby obstacles, etc. The various different approaches, rule-based, example-based or other, all define their responses by taking into account these particular sensory inputs.

In our latest experiments we aim to determine which of a set of sensory inputs affect an agent’s behavior and at what level. Using videos of real and simulated crowds, the steering behavior (i.e. trajectories) of the people are tracked and time sampled. At each sample, the surrounding stimuli of each person and their actions are recorded. These samples are then used as the input of a regression algorithm that learns a function that can map new input states (stimuli) to new output values (speed, direction). A series of different simulations are conducted with different time varying stimuli each time in order to extract all the necessary information.
Identifying the most important factors that affect good steering behaviors can help in the design of better rule based or example based simulation systems. In addition they can help improve crowd evaluation methods.

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Learning Crowd Behavior.

Panayiotis Charalambous and Yiorgos Chrysanthou. Workshop on Crowd Simulation (co-located with CASA 2010), 2010

We present here our ongoing work on learn-ing crowd behavior. The steering behavior of crowds from various video sources is tracked and databases of examples are gener-ated. These examples contain various stimuli (metrics) that could affect the persons behavior. These databases are used to learn rules for crowd steering in an agent based framework using re-gression algorithms and more specifically, decision trees. Various simulations are run and the statistics measured at the simulation stage are compared to those of the original video to de-termine which stimuli affect an agents behavior the most.

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