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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

Rights

All rights reserved All rights reserved

Publisher

Durham University

Date Created

2016

File Details

Depositor

T. Breckon

Date Uploaded

11 May 2016, 00:05:24

Date Modified

17 May 2016, 14:05:39

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Characterization

File format: zip (ZIP Format)

Mime type: application/zip

File size: 176995960

Last modified: 2016:05:17 13:52:09+01:00

Filename: MovingObjectDataSet-Hamilton-Breckon-2016.zip

Original checksum: dd345967cd96a33f81c43ca284e4d08e