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Multi-modal big data management for film production

Kim, H, Pabst, S, Sneddon, J, Waine, T, Clifford, J and Hilton, A (2015) Multi-modal big data management for film production In: 2015 IEEE International Conference on Image Processing (ICIP), 27-30 Sept. 2015, Quebec City, Canada.

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Modern digital film production uses large quantities of data from videos, digital photographs, LIDAR scans, spherical photography and many other sources to create the final film frames. The processing and management of this massive amount of heterogeneous data consumes enormous resources. We propose an integrated pipeline for 2D/3D data registration for film production. We present the prototype application Jigsaw, which allows users to efficiently manage and process various data from digital photographs to 3D point clouds. A key requirement in the use of multi-modal 2D/3D data for content production is the registration into a common coordinate frame. 3D geometric information is reconstructed from 2D data and registered to the reference 3D models using 3D feature matching. We provide a public multi-modal database captured with a wide variety of devices in different environments to assist further research. An order of magnitude gain in efficiency is achieved with the proposed approach.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Kim, H
Pabst, S
Sneddon, J
Waine, T
Clifford, J
Hilton, A
Date : 27 September 2015
Additional Information : © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 03 Nov 2015 10:47
Last Modified : 31 Oct 2017 17:48

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