Simple Search:

Speeded up surveillance video indexing and retrieval using abstraction


Citation

Chamasemani, Fereshteh Falah and Affendey, Lilly Suriani and Mustapha, Norwati and Khalid, Fatimah (2017) Speeded up surveillance video indexing and retrieval using abstraction. In: 2017 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2017), 12-14 Sept. 2017, Kuching, Sarawak. (pp. 374-378).

Abstract / Synopsis

Many researches have been conducted on video abstraction for quick viewing of video archives, however there is a lack of approach that considers abstraction as a pre-processing stage in video analysis. This paper aims to investigate the efficiency of integrating video abstraction in surveillance video indexing and retrieval framework. The basic idea is to reduce the computational complexity and cost of overall processes by using the abstract version of the original video that excludes unnecessary and redundant information. The experimental results show a significant reduction of 87% in computational cost by using the abstract video rather than the original video in both indexing and retrieval processes.


Download File

[img]
Preview
PDF (Abstract)
Speeded up surveillance video indexing and retrieval using abstraction.pdf

Download (34kB) | Preview

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1109/ICSIPA.2017.8120639
Publisher: IEEE
Keywords: Video abstraction; Surveillance video; Video indexing; Video retrieval; Video indexing and retrieval
Depositing User: Nabilah Mustapa
Date Deposited: 06 Mar 2018 14:40
Last Modified: 06 Mar 2018 14:40
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/ICSIPA.2017.8120639
URI: http://psasir.upm.edu.my/id/eprint/59466
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item