How Responsiveness, Group Membership and Gender Affect the Feeling of Presence in Immersive Virtual Environments Populated With Virtual Crowds
Marios Kyriakou and Yiorgos Chrysanthou
Presented at: ACM SIGGRAPH Conference on Motion, Interaction, and Games, MIG'18, Limassol, Cyprus, Nov 2018
Inverse Kinematics Techniques in Computer Graphics: A Survey
Andreas Aristidou, Joan Lasenby, Yiorgos Chrysanthou, Ariel Shamir
Computer Graphics Forum, 37(6): 35-58, Sep 2018
Presented at: Eurographics 2018 (STAR paper).
In this survey, we present a comprehensive review of the IK problem and the solutions developed over the years from the computer graphics point of view. The most popular IK methods are discussed with regard to their performance, computational cost and the smoothness of their resulting postures, while we suggest which IK family of solvers is best suited for particular problems. Finally, we indicate the limitations of the current IK methodologies and propose future research directions.
Self-similarity Analysis for Motion Capture Cleaning
Andreas Aristidou, Daniel Cohen-Or, Jessica K. Hodgins, Ariel Shamir
Computer Graphics Forum, 37(2): 297-309, May 2018
Presented at: Eurographics 2018
Our method automatically analyzes mocap sequences of closely interacting performers based on self-similarity. We define motion-words consisting of short-sequences of joints transformations, and use a time-scale invariant similarity measure that is outlier-tolerant to find the KNN. This allows detecting abnormalities and suggesting corrections.
Virtual Environment Navigation Assisted by Neural Networks
Georgios Kyrlitsias, Amyr Borges Fortes Neto, Panayiotis Charalambous, Marios Avraamides, Yiorgos Chrysanthou
Presented at: Virtual Humans and Crowds for Immersive Environments (VHCIE '18), May 2018
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.
Hand Tracking with Physiological Constraints
The Visual Computer, 34(2): 213-228, Jan 2018
We present a simple and efficient methodology for tracking and reconstructing 3D hand poses. Using an optical motion capture system, where markers are positioned at strategic points, we manage to acquire the movement of the hand and establish its orientation using a minimum number of markers. An Inverse Kinematics solver was then employed to control the postures of the hand, subject to physiological constraints that restrict the allowed movements to a feasible and natural set.
Emotion Control of Unstructured Dance Movements
Andreas Aristidou, Qiong Zeng, Efstathios Stavrakis, KangKang Yin, Daniel Cohen-Or, Yiorgos Chrysanthou, Baoquan Chen
Presented at: ACM SIGGRAPH/ Eurographics Symposium on Computer Animation, SCA'17. Eurographics Association, Jul 2017
We present a motion stylization technique suitable for highly expressive mocap data, such as contemporary dances. The method varies the emotion expressed in a motion by modifying its underlying geometric features. Even non-expert users can stylize dance motions by supplying an emotion modification as the single parameter of our algorithm.
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.