The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Scalable Big Data Pipeline for Video Stream Analytics Over Commodity Hardware
Abstract
A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology.Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making.Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details.In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment.Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.
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“Despite advancements in deepfake detection methods, significant research gaps exist, demanding concerted efforts to mitigate their potential harm (Ayub, SM & Qureshi, 2022).”
From Deepfake forensics: a survey of digital forensic methods for multimodal deepfake identification on social media (2024) · cites this paper as Ayub, SM & Qureshi, 2022
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Cites
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Converting video formats with FFmpeg
Tomar, S. (2006) · Linux journal · Cited by 278
Edge Video Analytics for Public Safety: A Review
Zhang, Q., Sun, H., Wu, X., & Zhong, H. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2925910 · Cited by 156
Design and Performance Evaluation of Image Processing Algorithms on GPUs
Park, I. K., Singhal, N., Lee, M. H., Cho, S., & Kim, C. (2010) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2010.115 · Cited by 154
Scalable 360° Video Stream Delivery: Challenges, Solutions, and Opportunities
Zink, M., Sitaraman, R. K., & Nahrstedt, K. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2894817 · Cited by 125
Anjum, A., Abdullah, T., Tariq, M. F., Baltacı, Y., & Antonopoulos, N. (2016) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2016.2517653 · Cited by 99
Using graphics devices in reverse: GPU-based Image Processing and Computer Vision
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Scaling Video Analytics Systems to Large Camera Deployments
Jain, S., Ananthanarayanan, G., Jiang, J., Shu, Y., & Gonzalez, J. E. (2019) · IEEE Workshop on Mobile Computing Systems and Applications (WMCSA) · doi:10.1145/3301293.3302366 · Cited by 71
Image parallel processing based on GPU
Zhang, N., Chen, Y., & Wang, J. (2010) · International Conference on Advanced Computer Control · doi:10.1109/icacc.2010.5486836 · Cited by 68
Canny edge detection and Hough transform for high resolution video streams using Hadoop and Spark
Iqbal, B., Iqbal, W., Khan, N., Mahmood, A., & Erradi, A. (2019) · Cluster Computing · doi:10.1007/s10586-019-02929-x · Cited by 55
Research works printed but not linked: 4
- Martin Gill and Angela Spriggs, Assessing the impact of CCTV, vol. 292, Home Office Research, Development and Statistics Directorate London, 2005.
- J. Kreps, N. Narkhede, and J. Rao, Kafka: "A distributed messaging system for log processing," in Proc. of 6th International Work-shop on Networking Meets Databases (NetDB), Athens, Greece, 2011.
- Chris Sweeney, Liu Liu, Sean Arietta, and Jason Lawrence, "Hipi: a hadoop image processing interface for image-based mapreduce tasks," Chris. University of Virginiam, vol. 2, no. 1, pp. 1-5, 2011.
- Helly M Patel, Krunal Panchal, Prashant Chauhan, and MB Potdar, "Large scale image processing using distributed and parallel architecture," International Journal of Computer Science and Information Technologies, Gujrat, India, vol. 6, no. 6, pp. 5531-5535, 2015.
Cited by
Qureshi, S. M., Saeed, A., Almotiri, S. H., Ahmad, F., & Al Ghamdi, M. A. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2037 · Cited by 71
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Metadata
- Venue
- KSII Transactions on Internet and Information Systems
- Published
- 2022-04-30
- Volume
- 16
- Issue
- 4
- ISSN
- 1976-7277
- Cited by
- 3
- References
- 15
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