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.
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.
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.
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.
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
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.
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.