Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow - Evaluation Dataset

Breckon, Toby P. (Durham University, UK); Hamilton, O.K. (Durham University, UK)

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Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow - Evaluation Dataset Open Access

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 therein, 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 motion relative to scene depth and camera motion. By leveraging both stereo odometry to recover camera motion in scene space and our stereo disparity to recover synthesised optic flow over the same in pixel space we isolate regions of inconsistency in depth an 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 using this evaluation dataset. Used in the paper: Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow (O.K. Hamilton, T.P. Breckon), In Proc. International Conference on Image Processing, IEEE, 2016.

Descriptions

Resource type: Dataset
Contributors: Creator: Hamilton, O.K. ¹
Creator: Breckon, Toby P. ¹
Contact person: Breckon, Toby P. ¹

¹ Durham University, UK
Funder: Engineering and Physical Sciences Research Council
Research methods
Other description
Keyword: computer vision
image processing
3D
object removal
scene mapping
automotive vision
stereo vision
Subject: Engineering
Computer Science
Location: Durham, England, United Kingdom
Language: England
Cited in: Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow (O.K. Hamilton, T.P. Breckon), In Proc. International Conference on Image Processing, IEEE, 2016.
Identifier: doi:10.15128/1544bp08d
ark:/32150/1544bp08d
Publisher: Durham University
Date Created: 2016

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Depositor: T. Breckon
Date Uploaded: 11 May 2016, 00:05:24
Date Modified: 17 May 2016, 14:05:39
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Last modified: 2016:05:17 13:52:09+01:00

Filename: MovingObjectDataSet-Hamilton-Breckon-2016.zip

Original checksum: dd345967cd96a33f81c43ca284e4d08e

Activity of users you follow
User Activity	Date
User O. Hamilton has added a new version of Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow - Evaluation Dataset	over 8 years ago
User T. Breckon has updated Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow - Evaluation Dataset	over 8 years ago
User O. Hamilton has added a new version of Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow - Evaluation Dataset	over 8 years ago
User O. Hamilton has updated Generalized Dynamic Object Removal for Dense Stereo Vision Based Scene Mapping using Synthesised Optical Flow - Evaluation Dataset	over 8 years ago