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Proceedings ArticleDOI

Intelligent video surveillance system in factory based on TLD algorithm

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TLDR
A real-time TLD motion detection and tracking algorithm is adopted and it is proved that the intelligent video monitoring system has good real- time and high accuracy.
Abstract
There are many key device nodes in factory, in order to ensure these devices working in a safe and stable way, we need to monitor the status of this devices in real-time. The system based on the video surveillance and computer vision methods, to monitor real-time status of equipment and give some feedback to central control room automatically. The web camera site obtains the video information and send it to the monitoring terminal. According to the properties and operational modes of the monitoring targets in a different way, the function of web camera sites can be personalized customization. This paper focuses on the detection and tracking algorithm of moving object in intelligent video surveillance. A real-time TLD motion detection and tracking algorithm is adopted. It is proved that the intelligent video monitoring system has good real-time and high accuracy.

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Citations
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Proceedings ArticleDOI

Reliability Analysis of Io VT Based Intelligent Video Surveillance System

TL;DR: The reliability of the intelligent VSS is analyzed in this paper, followed by a complete guideline to improve the current reliability and a different framework to analyze the system via the concept of reliability.
Journal Article

Tracking and video surveillance activity analysis

TL;DR: A system for detecting noteworthy behaviours (from a security or surveillance perspective) which does not involve the enumeration of the event sequences of all possible activities of interest and instead the focus is on calculating a measure of the abnormality of the action taking place.
References
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Book

Compressed sensing

TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Journal ArticleDOI

Incremental Learning for Robust Visual Tracking

TL;DR: A tracking method that incrementally learns a low-dimensional subspace representation, efficiently adapting online to changes in the appearance of the target, and includes a method for correctly updating the sample mean and a forgetting factor to ensure less modeling power is expended fitting older observations.
Book ChapterDOI

Real-time compressive tracking

TL;DR: A simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from the multi-scale image feature space with data-independent basis that performs favorably against state-of-the-art algorithms on challenging sequences in terms of efficiency, accuracy and robustness.
Journal ArticleDOI

Online selection of discriminative tracking features

TL;DR: This paper presents an online feature selection mechanism for evaluating multiple features while tracking and adjusting the set of features used to improve tracking performance, and notes susceptibility of the variance ratio feature selection method to distraction by spatially correlated background clutter.
Journal ArticleDOI

Robust online appearance models for visual tracking

TL;DR: A framework for learning robust, adaptive, appearance models to be used for motion-based tracking of natural objects to provide robustness in the face of image outliers, while adapting to natural changes in appearance such as those due to facial expressions or variations in 3D pose.
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