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Next generation motion controller and synthesis for game characters

Détails de la recherche
Numéro de l'application : 505237-2016
Année de concours : 2016 Année financière : 2018-2019
Nom de la personne : Popa, Tiberiu Institution : Concordia University
Département : Computer Science and Software Engineering Province : Québec
Montant : 48 000 $ Versement : 2 - 2
Type de programme : Subventions de recherche et développement coopérative Comité évaluateur : Cté de décision interne - PPR
Sujet de recherche : Infographie Domaine d'application : Technologie de l'information, des ordinateurs et des réseaux de communications
Chercheurs associés : Mudur, Sudhir Pandurang SP
Partenaires : Ubisoft divertissement inc.
Sommaire du projet

Animation is a quintessential part of game playing experience since the dawn of computer gaming. With recent advances in animation acquisition and synthesis, computer animation in games is getting more and more complex and more and more realistic. This realism comes at a cost: the computational and memory requirements for new games are very high. The goal of this project is to propose a new type of animation controller for games that increases the realism of the animation while, at the same time, significantly reduces the computational and memory footprints. ****We achieve this by using recent advances in artificial intelligence and neural networks. Current state of the art animation controllers store pre-recorded animations in memory, and at run-time they stitch them together to synthesize a new motion that conforms to the constraints that the character has such as terrain, collision with other objects, etc. In this work, instead of carrying all these pre-recorded animation in memory and using them to synthesize new motion, we will use them to learn the motion of a given character using state of the art deep learning techniques. Once the motion is learned, the synthesis is light-weight, and does not have a large memory footprint. Furthermore, the motion synthesis using neural networks is achieved by querying the neural network. This operation can be easily moved onto the cloud allowing the gaming console to release a lot of the processing time to other tasks. ****The learning stage, on the other hand, is difficult and computationally expensive, but it needs to be done only once in an off-line manner and it can be done by the gaming company using a centralized cluster of computers. Using this new game controller concept effectively shifts the complexity of the process to an off-line process, leaving only light tasks to be performed in real-time. ****We are collaborating closely on this project with UBISOFT, a leading company in computer games that has a large R&D studio in Montreal. Using this technique will achieve a significant paradigm shift in computer animation that has the potential of revolutionizing the computer gaming field thus benefiting the company, the computer animation community as well as the Canadian gaming industry as a whole. ************