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Generalized dynamic object removal for dense stereo vision based scene mapping using synthesised optical flow.

Hamilton, O.K. and Breckon, T.P. (2016) 'Generalized dynamic object removal for dense stereo vision based scene mapping using synthesised optical flow.', in 2016 IEEE International Conference on Image Processing (ICIP), September 25-28, 2016, Phoenix, Arizona, USA ; proceedings. Piscataway, NJ: IEEE, pp. 3439-3443.


Mapping an ever changing urban environment is a challenging task as we are generally interested in mapping the static scene and not the dynamic objects, such as cars and people. We propose a novel approach to the problem of dynamic object removal within stereo based scene mapping that is both independent of the underlying stereo approach in use and applicable to varying object and camera motion. By leveraging stereo odometry, to recover camera motion in scene space, and stereo disparity, to recover synthesised optic flow over the same pixel space, we isolate regions of inconsistency in depth and image intensity. This allows us to illustrate robust dynamic object removal within the stereo mapping sequence. We show results covering objects with a range of motion dynamics and sizes of those typically observed in an urban environment.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Publisher statement:© 2016 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.
Date accepted:12 July 2016
Date deposited:03 October 2016
Date of first online publication:19 August 2016
Date first made open access:No date available

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