Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow
Hamilton, O.K.; Breckon, T.P.
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.
Hamilton, O., & Breckon, T. (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 (3439-3443). https://doi.org/10.1109/icip.2016.7532998
|Conference Name||2016 IEEE International Conference on Image Processing.|
|Conference Location||Phoenix, AZ, USA|
|Start Date||Sep 25, 2016|
|End Date||Sep 28, 2016|
|Acceptance Date||Jul 12, 2016|
|Online Publication Date||Aug 19, 2016|
|Publication Date||Aug 19, 2016|
|Deposit Date||Oct 3, 2016|
|Publicly Available Date||Oct 3, 2016|
|Book Title||2016 IEEE International Conference on Image Processing (ICIP), September 25-28, 2016, Phoenix, Arizona, USA ; proceedings.|
|Related Public URLs||http://community.dur.ac.uk/toby.breckon/publications/papers/hamilton16removal.pdf|
Accepted Conference Proceeding
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