Motion capture (mocap) is the technological process used for acquiring three-dimensional (3D) positioning and orientation information of a moving object. Due to the high quality of capture and portrayal of movements, it has found applications in many areas including entertainment, media, military, sports, rehabilitation, and medical sciences.
We have recently equipped with the new Phasespace Impulse X2E motion capture system with active LEDs, establishing our motion capture studio in collaboration with the CYENS Centre of Excellence. Our Phasespace Impulse X2E system costists 24 cameras that are able to capture 3D motion using modulated LEDs. These cameras contain a pair of linear scanner arrays operating at high frequency each of which can capture the position of any number of bright spots of light as generated by the LEDs. The system offers a fast rate of capture (up to 960Hz) and allows the individual markers to be identified by combining the information from several frames and hence identifying the marker from its unique modulation.
In our lab, we are investigating novel methods for motion skeletal reconstruction, motion data cleaning, and looking forward to find innovative and effective approaches for human mesh reconstruction, including body deformations.
In our lab, we are investigating novel and effective methods in character animation, at the intersection of computer vision and graphics. More specifically, we are interested in methods and applications in the wider area of character animation, including motion reconstruction, motion analysis segmentation, and documentation, emotion recognition, style tranfer, motion retargeting, motion synthesis, and motion interaction. More recently, we have developed innovative frameworks using convolutional or reccurent neural networks, generative adversarial networks; we are also interested in working with reinforcement learning, and physics-based animations.
Over the last few decades, a number of methods have been proposed to record, e-document, preserve, protect and disseminate mostly tangible cultural heritage. Apart thought from the tangible artifacts, cultural heritage also encompasses a range of important intangible assets that includes collective knowledge of communities, skills, practices, expressions, art, fashion and representations that do not have a tangible form. Intangible Cultural Heritage (ICH) is a mainspring of humanity’s cultural diversity and its maintenance is a guarantee for continuing creativity. In this direction, we are investigating methods and developing applications that contribute in the hollisting acquisition, documentation, reconstruction, analysis, synthesis, and visualization of intangible creations, and more specifically, folk dancing.
Using the motion capture technology, our lab has created a point-of-reference publicly accessible digital archive of folk dances. Several virtual and augmented applications have been developed, including a virtual dance museum and an e-learning dance simulator for teaching users folk dancing. We have also created the digital dance ethnography, by contextually analyzing dance, and have examined the evolution of dancing over the time, and among neighboring countries.
Geometric Algebra (GA) provides a convenient mathematical notation for representing orientations and rotations of objects in three dimensions. The conformal model of GA (CGA) is a mathematical framework that offers a compact and geometrically intuitive formulation of algorithms, and an easy and immediate computation of rotors. Rotors are simpler to manipulate than Euler angles, and they are more numerically stable and efficient than rotation matrices, avoiding the problem of gimbal lock.
Geometric algebra is particularly well suited to allow cross-disciplinary solutions in software engineering as it provides an intuitive and insightful common denominator across mathematical disciplines used in a variety of applications. Understanding GA enables us to relate distinct, seemingly incompatible paths by providing a common geometric and mathematical base. CGA gives us also the ability to describe algorithms in a geometrically intuitive and compact manner, making it suitable for applications in engineering, computer vision, graphics, and robotics.
We offer several courses related to computer graphics, character animation, computer games, computer vision, and motion capturing.