Improving Tracking Accuracy Using Illumination Neutralization and High-Dynamic Range Imaging

Nikolas Ladas, Yiorgos Chrysanthou, Celine Loscos

High Dynamic Range Video Concepts, Technologies and Applications, ed. by Alan Chalmers, Patrizio Campisi, Peter Shirley, and Igor Olaizola. 1st edition. Academic Press. pp. 203–213, Jun 2017


Probabilistic Background Modelling for Sports Video Segmentation

Nikolas Ladas, Paris Kaimakis, Yiorgos Chrysanthou

Presented at: 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, pp 517-525, Porto, Portugal, Jan 2017


Continuous body emotion recognition system during theater performances

Simon Senecal, Louis Cuel, Andreas Aristidou, Nadia Magnenat-Thalmann

Comp. Animation & Virtual Worlds, 27(3-4): 311-320, May 2016

Presented at: Computer Animation and Social Agents - CASA'16

We propose a system for continuous emotional behavior recognition expressed by people during communication based on their gesture and their whole body dynamical motion. The features used to classify the motion are inspired by the Laban Movement Analysis. Using a trained neural network and annotated data, our system is able to describe the motion behavior as trajectories on the Russell Circumplex Model diagram during theater performances over time.

DOI paper bibtex

Extending FABRIK with Model Constraints

Andreas Aristidou, Yiorgos Chrysanthou, Joan Lasenby

Comp. Animation & Virtual Worlds, 27(1): 35-57, Jan 2016

This paper addresses the problem of manipulating articulated figures in an interactive and intuitive fashion for the design and control of their posture using the FABRIK algorithm; the algorithm has been extended to support a variation of different joints and has been evaluated on a humanoid model.

DOI paper video bibtex project page

Data Driven Crowd Evaluation

Panayiotis Charalambous, Yiorgos Chrysanthou

Simulating Heterogeneous Crowds with Interactive Behaviors. Ed. by Nuria Pelechano, Jan M. Allbeck, Mubbasir Kapadia, and Badler Norman I. CRC Press. Chap. 10, pp. 217–237, Jan 2016


Learning Heterogeneous Crowd Behavior from the Real World

Panayiotis Charalambous, Yiorgos Chrysanthou

Simulating Heterogeneous Crowds with Interactive Behaviors. Ed. by Nuria Pelechano, Jan M. Allbeck, Mubbasir Kapadia, and Badler Norman I. CRC Press. Chap. 3, pp. 53–73, Jan 2016


Folk Dance Evaluation Using Laban Movement Analysis

Andreas Aristidou, Efstathios Stavrakis, Panayiotis Charalambous, Yiorgos Chrysanthou, Stephania L. Himona

ACM Journal on Computing and Cultural Heritage, 8(4): 1-19, Aug 2015

Presented at: Best paper award at EG GCH 2014.

We present a framework based on the principles of Laban Movement Analysis (LMA) that aims to identify style qualities in dance motions, 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.

DOI paper video bibtex project page

Emotion analysis and classification: Understanding the performers’ emotions using LMA entities

Andreas Aristidou, Panayiotis Charalambous, Yiorgos Chrysanthou

Computer Graphics Forum, 34(6): 262–276, Apr 2015

Presented at: Eurographics 2016

We proposed a variety of features that encode characteristics of motion, in terms of Laban Movement Analysis, for motion classification and indexing purposes. Our framework can be used to extract both the body and stylistic characteristics, taking into consideration not only the geometry of the pose but also the qualitative characteristics of the motion. This work provides some insights on how people express emotional states using their body, while the proposed features can be used as alternative or complement to the standard similarity, motion classification and synthesising methods.

DOI paper video database bibtex project page

Interaction with virtual agents – Comparison of the participants’ experience between an IVR and a semi-IVR system

Marios Kyriakou, Xueni Pan, Yiorgos Chrysanthou

Presented at: IEEE Virtual Reality (VR) conference. IEEE. pp. 217–218, Mar 2015


Toward Energy-Aware Balancing of Mobile Graphics

Efstathios Stavrakis, Marios Polychronis, Nectarios Pelekanos, Alessandro Artusi, Panayiotis Hadjichristodoulou, Yiorgos Chrysanthou

Presented at: Mobile Devices and Multimedia: Enabling Technologies, Algorithms and Applications, SPIE 9411, Mar 2015


LMA-Based Motion Retrieval for Folk Dance Cultural Heritage

Andreas Aristidou, Efstathios Stavrakis, Yiorgos Chrysanthou

LNCS, volume 8740, pages 207-216, Nov 2014

Presented at: 5th International Conference on Cultural Heritage (EuroMed'14), Limassol, Cyprus

DOI paper bibtex

A Data‐Driven Framework for Visual Crowd Analysis

Panayiotis Charalambous, Ioannis Karamouzas, Stephen J. Guy, Yiorgos Chrysantho

Computer Graphics Forum, vol. 33, no. 7, pp. 41-50, Oct 2014

Presented at: Pacific Graphics 2014

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.

DOI paper video project page

Motion Analysis for Folk Dance Evaluation

Andreas Aristidou, Efstathios Stavrakis, Yiorgos Chrysanthou

Presented at: 12th EUROGRAPHICS Workshop on Graphics and Cultural Heritage (GCH'14), pages 55-64, Darmstadt, Germany, Oct 2014

DOI paper bibtex

Automatic Emotion Recognition Based on Body Movement Analysis: A Survey

Haris Zacharatos, Christos Gatzoulis, Yiorgos Chrysanthou

IEEE Computer Graphics and Applications 34.6 (2014), pp. 35–45, Sep 2014


The PAG Crowd: A Graph Based Approach for Efficient Data‐Driven Crowd Simulation.

Panayiotis Charalambous, Yiorgos Chrysanthou.

Computer Graphics Forum, vol. 33, no. 8, pp. 95-108, Jun 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.

DOI paper video project page