loading
Documents

Research.Publish.Connect.

Paper

Authors: Priyam Bakliwal 1 ; Guruprasad M. Hegde 2 and C. V. Jawahar 1

Affiliations: 1 International Institute of Information Technology, India ; 2 Bosch Research and Technology Centre, India

ISBN: 978-989-758-227-1

Keyword(s): Video-processing, Active-leaning, Surveillance Video Annotations, Tracking.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Tracking and Visual Navigation ; Video Surveillance and Event Detection

Abstract: We propose an active learning based solution for efficient, scalable and accurate annotations of objects in video sequences. Recent computer vision solutions use machine learning. Effectiveness of these solutions relies on the amount of available annotated data which again depends on the generation of huge amount of accurately annotated data. In this paper, we focus on reducing the human annotation efforts with simultaneous increase in tracking accuracy to get precise, tight bounding boxes around an object of interest. We use a novel combination of two different tracking algorithms to track an object in the whole video sequence. We propose a sampling strategy to sample the most informative frame which is given for human annotation. This newly annotated frame is used to update the previous annotations. Thus, by collaborative efforts of both human and the system we obtain accurate annotations with minimal effort. Using the proposed method, user efforts can be reduced to half without com promising on the annotation accuracy. We have quantitatively and qualitatively validated the results on eight different datasets. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.172.234.236

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Bakliwal, P.; M. Hegde, G. and Jawahar, C. (2017). Collaborative Contributions for Better Annotations.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 353-360. DOI: 10.5220/0006098103530360

@conference{visapp17,
author={Priyam Bakliwal. and Guruprasad M. Hegde. and C. V. Jawahar.},
title={Collaborative Contributions for Better Annotations},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={353-360},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006098103530360},
isbn={978-989-758-227-1},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - Collaborative Contributions for Better Annotations
SN - 978-989-758-227-1
AU - Bakliwal, P.
AU - M. Hegde, G.
AU - Jawahar, C.
PY - 2017
SP - 353
EP - 360
DO - 10.5220/0006098103530360

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.