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

Cypriot Intangible Cultural Heritage: Digitizing Folk Dances

Andreas Aristidou, Efstathios Stavrakis, Yiorgos Chrysanthou

Cyprus Computer Society journal, Issue 25, pages 42-49, Apr 2014

We aim to preserve the Cypriot folk dance heritage, creating a state-of-the-art publicly accessible digital archive of folk dances. Our dance library, apart from the rare video materials that are commonly used to document dance performances, utilises three dimensional motion capture technologies to record and archive high quality motion data of expert dancers.

paper bibtex project page

Simulating Heterogeneous Crowds With Interactive Behaviors

Mubbasir Kappadia, Nuria Pelechano, Stephen Guy, Jan Allbeck, Yiorgos Chrysanthou

Presented at: Tutorial at Eurographics’14, Apr 2014


Feature extraction for human motion indexing of acted dance performances

Andreas Aristidou, Yiorgos Chrysanthou

Presented at: 9th International Conference on Computer Graphics Theory and Applications (GRAPP'14), pages 277-287, Lisbon, Portugal, Jan 2014

DOI paper bibtex

Motion indexing of different emotional states using LMA components

Andreas Aristidou, Yiorgos Chrysanthou

Presented at: SIGGRAPH Asia Technical Briefs (SA’13), ACM, New York, USA, 21:1-21:4, Nov 2013

DOI paper bibtex

Emotion Recognition for Exergames using Laban Movement Analysis

Haris Zacharatos, Christos Gatzoulis, Yiorgos Chrysanthou, Andreas Aristidou

Presented at: ACM Motion in Games (MIG'13), Dublin, Ireland, Sep 2013

DOI paper bibtex

Learning Through Multi-Touch Interfaces in Museum Exhibits: an Empirical Investigation

Panagiotis Zaharias, Despina Michael, Yiorgos Chrysanthou

Educational Technology & Society 16.3 (2013), pp. 374–384, Sep 2013


Marker Prediction and Skeletal Reconstruction in Motion Capture Technology

Andreas Aristidou, Yiorgos Chrysanthou

Tech. rep. UCY-CS-TR-13-2. University of Cyprus, Aug 2013

paper bibtex