My main interests are focused on 3D motion analysis and classification, motion synthesis, human animation, and involve motion capture, inverse kinematics, and applications of conformal geometric algebra in graphics.
Although modern technologies such as GPS and accelerometers have revolutionized the field of animal monitoring and habitat utilization, there have been technical limitations preventing their use for small-sized reptiles. The general objective of this project is to tackle this problem and to advance scientific knowledge in the fields of (a) reptile locomotion (b) behavioral analysis and (c) conservation, through the development of innovative monitoring techniques and approaches. The project will take place in Cyprus using two common species, a lizard (Stellagama stellio) and a snake (Dolichophis jugularis). For achieving these objectives two innovative techniques will be established. The first aims to assist in the semi-autonomous and continuous remote tracking of reptiles to obtain finescale locomotion data. This technique will be based on Angle-of-Arrival measurements acquired through Radio Direction Finding (RDF) technology which is able to calculate and project the location of a VHF transmitter on a digital map. The second focuses on semi-autonomously recognizing and categorizing behavioral patterns of reptiles, tagged with small-size accelerometers This technique relies on analyzing acceleration curves through the use of pattern recognition software and linking them with a predefined behavioral pattern database. The combination of these techniques with state-of-the-art technology in remote sensing, advanced photogrammetry and image pattern recognition will allow the creation of fine-scale micro-habitat utilization maps, advancing site level management through the designing of more targeted, species based management and conservation actions. For the successful implementation of this project, a number of activities are being put forth including developing of innovative tools, monitoring of reptiles, analyzing acceleration curves and developing algorithms for predicting animals’ movements. Both techniques when fully developed will be tested in the field through a case study and their abilities for enhancing conservation delivery will be evaluated.
More details about my involvement in the project can be found at the behavioral analysis section of the project.
Dance is an integral part of any culture. Through its choreography and costumes dance imparts richness and uniqueness to that culture. Over the last decade, technological developments have been exploited to record, curate, remediate, provide access, preserve and protect tangible CH. However, intangible assets, such as dance, has largely been excluded from this previous work. UNESCO states in its 2003 Convention for the Safeguarding of the Intangible Cultural Heritage (ICH) that ICH is a mainspring of humanity's cultural diversity and its maintenance is a guarantee for continuing creativity. However, modern factors such as globalization and the massive movement of people have diminished the unique culture of many communities, and indeed there is a now a very real risk that many types of ICH may disappear forever. Recent computing advances have enabled the accurate 3D digitization of human motion. Such systems provide a new means for capturing, preserving and subsequently re-creating ICH which goes far beyond traditional written or imaging approaches. However, 3D motion data is expensive to create and maintain, encompassed semantic information is difficult to extract and formulate, and current software tools to search and visualize this data are too complex for most end-users. SCHEDAR will provide novel solutions to the three key challenges of archiving, re-using and re-purposing, and ultimately disseminating ICH motion data. In addition, we will devise a comprehensive set of new guidelines, a framework and software tools for leveraging existing ICH motion databases. Data acquisition will be undertaken holistically; encompassing data related to the performance, the performer, the kind of the dance, the hidden/untold story, etc. Innovative use of state-of-the-art multisensory Augmented Reality technology will enable direct interaction with the dance, providing new experiences and training in traditional dance which is key to ensure this rich culture asset is preserved for future generations.
ITN-DCH aims -for the first time worldwide- to analyze, design, research, develop and validate an innovative multi-disciplinary and inter-sectorial research training framework that covers the entire lifecycle of digital CH research for a cost–effective preservation, documentation, protection and presentation of cultural heritage. CH is an integral element of Europe and vital for the creation of a common European identity and one of the greatest assets for steering Europe’s social, economic development and job creation. However, the current research training activities in CH are fragmented and mostly design to be of a single-discipline, failing to cover the whole lifecycle of Digital Cultural Heritage (DCH) research, which is by nature a multi-disciplinary and inter-sectorial research agenda.
This project aims at generating a virtual animated character that interacts, in real-time, with a real dancing performer to compose a contemporary dancing show. The proposed research will explore innovative topics with special interest in the area of computer animation, including methods which smoothly combine optical motion capture (mocap) data with kinematic techniques, human figure modelling, a novel methodology for motion classification and partial-body motion synthesis. The system will be adjusted dynamically according to the performers' actions and responses, offering the maximum possible interaction between the natural and virtual performer. Similar techniques can be adapted to the game industry, possibly for military or local law enforcement training simulators or other virtual character animations.
This project aims at creating a publicly accessible digital archive of dances using 3D motion capture data (with metadata); more emphasis will be given to Cypriot and Greek folk dancing.
This is an evolving project and data will be added to our database as we capture them over time.
Cyprus has a long and rich history of dance tradition which unfortunately, year after year, tends to be forgotten; thus, it is our duty to help documenting and disseminating our dance heritage to the younger generations. In this work, 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. Apart from the goal of preserving this intangible cultural heritage by digitizing it, the project is interested in increasing the awareness of the local community to its dance heritage. To achieve this a 3D video game for children is developed to teach these folk dances to the younger generations.
SimPol VR (Synthesis of Dynamic Characters with motion capture data for human figure animation: Educating the police force) is a research project funded by the Cyprus Research Promotion Foundation in the area of Computer Graphics and more specifically in the sub-area of Human Body Animation. The project focuses in investigating the usability and applicability of Virtual Reality in training special forces. It proposes the development of a platform using Computer Graphics techniques (as oppossed to the existing video-based system that is restrictive), for the creation of a 3D Visualisation Tool enriched with tools suitable for the formation and customisation of dynamic scenarios. The proposed platform will be used as a simulator for training purposes by the Cyprus Police Emergency Response Unit. The user of the platform will be able to fully participate, act and interact with the environment. To achieve the above, research will be carried out in the area of Computer Animation for realistic avatar movement as well as the realistic and dynamic change of facial expressions. Smoothing of the surfaces on the avatar models used is another area that will be targeted by this project work. Researchers from Frederick University, the University of Cyprus, P.A. College, the University of Nicosia and abroad will be involved as well as acting trainers from the Cyprus Police Emergency Response Unit.
Inverse Kinematics is defined as the problem of determining a set of appropriate joint configurations for which the end effectors move to desired positions as smoothly, rapidly, and as accurately as possible. However, many of the currently available methods suffer from high computational cost and production of unrealistic poses. In this work, a novel heuristic method, called Forward And Backward Reaching Inverse Kinematics (FABRIK), is described and compared with some of the most popular existing methods regarding reliability, computational cost and conversion criteria. FABRIK avoids the use of rotational angles or matrices, and instead finds each joint position via locating a point on a line. Thus, it converges in fewer iterations, has low computational cost and produces visually realistic poses. Constraints can easily be incorporated within FABRIK and multiple chains with multiple end effectors are also easily supported.
© 2017 Andreas Aristidou