The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Multiple Cameras Using Real Time Object Tracking for Surveillance and Security System
Abstract
In this paper we propose multiple cameras using real time tracking for surveillance and security system. It is extensively used in the research field of computer vision applications, like that video surveillance, authentication systems, robotics, pre-stage of MPEG4 image compression and user inter faces by gestures. The key components of tracking for surveillance system are extracting the feature, background subtraction and identification of extracted object. Video surveillance, object detection and tracking have drawn a successful increased interest in recent years. A object tracking can be understood as the problem of finding the path (i.e. trajectory) and it can be defined as a procedure to identify the different positions of the object in each frame of a video. Based on the previous work on single detection using single stationary camera, we extend the concept to enable the tracking of multiple object detection under multiple camera and also maintain a security based system by multiple camera to track person in indoor environment, to identify by my proposal system which consist of multiple camera to monitor a person. Present study mainly aims to provide security and detect the moving object in real time video sequences and live video streaming. Based on a robust algorithm for human body detection and tracking in videos created with support of multiple cameras.
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“The frame differencing and optical flow algorithms both compare consecutive frames to detect changes in pixel values, but optical flow algorithms are more suitable for dynamically changing environments, which can process complex motion patterns [69][70][71].”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [69]
Citations
Cites
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Background subtraction techniques: a review
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Human motion analysis: a review
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Crowd monitoring using image processing
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An Improved Moving Object Detection Algorithm Based on Frame Difference and Edge Detection
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Research works printed but not linked: 1
- mcivor, 0, Background Subtraction Techniques, Reveal Ltd PO Box 128-221 Remuera
Cited by
A Survey of Video Surveillance Systems in Smart City
Myagmar-Ochir, Y., & Kim, W. (2023) · Electronics · doi:10.3390/electronics12173567 · Cited by 134
Metadata
- Authors
- Susheel Kumar, K., Prasad, S., Saroj, P. K., & Tripathi, R. C.
- Affiliations
- Indian Institute of Information Technology Allahabad (IN)
- ORCID
- Prasad, S
- Venue
- 2010 3rd International Conference on Emerging Trends in Engineering and Technology
- Publisher
- IEEE
- Published
- 2010-11
- Pages
- 213-218
- OpenAlex
- W2129920697
- Cited by
- 32
- References
- 17
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 3 · 2022: 4 · 2021: 4 · 2020: 3 · 2017: 2 · 2016: 3 · 2015: 2 · 2014: 2 · 2013: 1 · 2012: 1
- FWCI
- 0.82
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Emerging Trends in Engineering and Technology (ICETET) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- multi-camera surveillance, real-time object tracking, video surveillance, background subtraction, human detection, human tracking, indoor monitoring, moving object detection, live streaming, security systems
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