Addictive Mobility is a leading (Big Data) online advertising company in Canada. They use real-time bidding (RTB) platform for online display advertising in mobile devices, where multiple companies compete to show a certain Ad to a specific user at a certain time. The goal is to optimize the system such that they minimize the cost over the campaign period but also send targeted ads to maximize return on investment such as number of clicks or purchases.

Addictive Mobility is a leading online advertising company in Canada. The success of ad campaigns drives the majority of the company revenue. Exploring advanced machine-learning techniques to efficiently control an ad's performance is crucial to the company strategy. The objective of the proposed project is to optimize the real-time bidding system in the sense that delivery has been carried out in real-time and within a time-interval of 100 ms.

The ultimate aim of this project is to design and develop methods and tools for classifying attributes of books such as genre, style, tone, and likelihood of being popular. Towards this end we will make use of various information types available on books and users of the Kobo catalog, including the text, meta-data associated with the text, and user features associated with readers of the text. This is a large undertaking.

Le projet consiste à créer un modèle 3D interactif du monastère des Ursulines de Québec pour une diffusion Web afin de mettre en valeur l’héritage des religieuses ainsi que son monastère (considéré comme un bien patrimonial national). Notre projet est avant-gardiste parce qu’il propose une libre navigation dans le modèle aux internautes. En effet, la reconstitution est construite sur une plate-forme jeu (gaming engine) permettant une meilleure fluidité et interactivité, tout en respectant l’authenticité des lieux réels.

deviantART is the world's largest online arts community with a huge number of users and items. They currently recommend art to users only via an algorithmic presentation of "popular" items, and an item-item recommender system presented alongside every individual piece of art. deviantART expects to use recommender systems technology to enhance and leverage the contributions of existing "Groups" of users.

CogniVue is a leading innovator in embedded computer vision, providing both hardware and software solutions that enable its customers to develop high-performance, low-power embedded vision applications. From the success of recent 3D sensing technologies such as the Microsoft Kinect or the Intel Creative camera, the need for innovative low-cost depth sensors is rapidly growing. In the range of 3D sensing technologies that are available stereo vision offers unique value propositions in terms of range, flexibility to lighting conditions, cost and power.

Le projet vise à concevoir une nouvelle télécommande de jeu interactive utilisant des fonctions inédites parmi les consoles de jeu existantes. Le design sera développé selon une approche centrée sur les utilisateurs afin d’assurer leur confort et le plaisir de jouer.

In partnership with Zenfri Inc, this project seeks to facilitate the successful introduction of a mobile game called Clandestine Anomaly to the mobile game market. Due to the embryonic stage of the mobile game market this research will use primary and secondary research methods to create a market analysis and inform the market strategy. Firstly, this research will provide an understanding of the business environment by analyzing successful products and their marketing strategies along with industry trends and characteristics.

LANGA is a project at Copernicus Studios (Halifax, NS) that is experimenting with the use of automated speech recognition in on-line video games to assist in language learning. Over the past 2 years, the company has been developing prototypes of the game and testing them in conjunction with the NeuroCognitive Imaging Lab at Dalhousie University. A key element to both the commercial success of the product and the research supporting its efficacy is scaling from lab-based testing of small numbers of people, to on-line delivery that supports thousands and possibly millions of users.

We propose to develop computer vision technologies for recognizing 3D environment for augmented reality (AR) mobile games. Given an image/video taken captured a mobile device (e.g. iPad), we would like to be able to recognize some useful information about the 3D environment of the game player. For example, one of our goals is to recognize whether the player is in an indoor or outdoor environment. This information will allow the game to project appropriate virtual objects and characters that interact with the user. Another goal is to recognize certain important objects (e.g.