Journal ArticleDOI
Smoke detection in video using wavelets and support vector machines
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TLDR
A novel method for smoke characterization using wavelets and support vector machines is proposed and the results are impressive with limited false alarms.About:
This article is published in Fire Safety Journal.The article was published on 2009-11-01. It has received 181 citations till now. The article focuses on the topics: Video processing.read more
Citations
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BookDOI
Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures
M. Jorge Cardoso,Tal Arbel,Xiongbiao Luo,Stefan Wesarg,Tobias Reichl,Miguel Ángel González Ballester,Jonathan McLeod,Klaus Drechsler,Terry M. Peters,Marius Erdt,Kensaku Mori,Marius George Linguraru,Andreas Uhl,Cristina Oyarzun Laura,Raj Shekhar +14 more
TL;DR: Experimental results show that the proposed method can effectively estimate the end-effector pose and delineate its boundary while being trained with moderately sized data clusters, and it is shown that matching such huge ensemble of templates takes less than one second on commodity hardware.
Journal ArticleDOI
Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection
TL;DR: An improved convolutional neural network model is designed for extracting smoke features and smoke detection and has a good detection performance on the smoke generated in the actual scenes and effectively reduces the false alarm rate.
Journal ArticleDOI
Early smoke detection in video using swaying and diffusion feature
TL;DR: A method of early smoke detection in video using swaying and diffusion feature is presented, and a swaying identification algorithm based on centroid calculation was used to distinguish candidate smoke region from other dynamic regions.
Posted Content
Machine Vision for Natural Gas Methane Emissions Detection Using an Infrared Camera
Jingfan Wang,Lyne P. Tchapmi,Arvind P. Ravikumara,Mike McGuire,Clay S. Bell,Daniel Zimmerle,Silvio Savarese,Adam R. Brandt +7 more
TL;DR: In this article, the authors developed a computer vision approach to OGI-based leak detection using convolutional neural networks (CNN) trained on methane leak images to enable automatic detection.
Posted Content
Industrial Smoke Detection and Visualization
TL;DR: A software tool which integrates an algorithm based on change detection and texture segmentation for identifying smoke emissions, an interactive timeline visualization providing indicators for seeking to interesting events, an autonomous fast-forwarding mode for skipping uninteresting timelapse frames, and a collection of animated smoke images generated automatically according to the algorithm are described.
References
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Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Journal ArticleDOI
Discrete Cosine Transform
TL;DR: In this article, a discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed, which can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering.
Book
Discrete Cosine Transform: Algorithms, Advantages, Applications
TL;DR: This paper presents two Dimensional DCT Algorithms and their relations to the Karhunen-Loeve Transform, and some applications of the DCT, which demonstrate the ability of these algorithms to solve the discrete cosine transform problem.
Journal ArticleDOI
A survey of video processing techniques for traffic applications
TL;DR: This paper presents an overview of image processing and analysis tools used in traffic applications and relates these tools with complete systems developed for specific traffic applications, and categorizes processing methods based on the intrinsic organization of their input data and the domain of processing.