Christie Digital Systems Usa, Inc.

Miovision Technologies Incorporated

Microtraffic Inc

Nicholas Jankovic

Justin A Eichel

Daniel Thomson Urquhart

Akshaya K Mishra

Nicholas Miller

Peter Anthony Van Eerd

Kevin R Moule

Derek Scott

Eliezer Azi Ben-Lavi

Kurtis N McBride

Ian Chadwyck Faragher

Ryan Thomas Morris

Anthony I Brijpaul

Douglas J Swanson

To address problems that video imaging systems and platforms face when analyzing image and video content for detection and feature extraction, a solution is provided in which accumulating significant amounts of data suitable for training and learning analytics is leveraged to improve over time, the classifiers used to perform the detection and feature extraction, by employing a larger search space and generate additional and more complex classifiers through distributed processing. A distributed learning platform is therefore provided, which is configured for operating on large scale data, in a true big data paradigm. The learning platform is operable to empirically estimate a set of optimal feature vectors and a set of discriminant functions using a parallelizable learning algorithm. A method of adding new data into a database utilized by such a learning platform is also provided. The method comprises identifying an unrepresented sample space; determining new data samples associated with the unrepresented sample space; and adding the new data samples to the database.

Machine learning platform for performing large scale data analytics

A system and method are provided for compressing video data, the method comprising: obtaining video data; extracting at least one object of interest from the video data using at least one classifier associated with at least one feature detectable in the video data; and preparing compressed video data comprising at least one object of interest extracted from the video data.

System and method for compressing video data

A method, system, and a computer readable medium for screen correction is provided. The system includes a memory storage unit for storing model content, a screen having screen parameters, an input device for receiving the screen parameters, a correction engine, and a projector. The method involves storing model content on a memory storage unit, receiving screen parameters, generating screen content, and projection at least a portion of the screen content onto the screen. The computer readable medium encoded with codes for directing a processor to carry out the method.

Method and system for screen correction

A system and method for aligning stacked projectors is provided. A computing device is in communication with at least two projectors, configured to project images stacked onto each other, and at least one sensor configured to acquire respective images the projector images. Respective initial positions in a common space are determined of each of the projector images, from the sensor images, as well as a virtual projector image located at a common target position. Respective transforms for each of the projector images to one or more of shift and transform the projector images to the common target position of the virtual projector image. The respective transforms are applied to further first projector images to produce respective transformed projector images. The projectors are controlled to project the respective transformed projector images according to the common target position.

System and method for aligning stacked projectors

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Waterloo, Canada

Nicholas Jankovic