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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Posted Content
Domain Adaptation from Synthesis to Reality in Single-model Detector for Video Smoke Detection
TL;DR: To train a strong detector with rich synthetic samples, the adaptation to the detection layer of state-of-the-art single-model detectors (SSD and MS-CNN) is constructed and the results show that the detectors based on the adversarial adaptation are superior to the detectorsbased on the discrepancy adaptation.
Journal ArticleDOI
Forest fire smoke detection under complex backgrounds using TRPCA and TSVB
TL;DR: A novel method that combines Time Domain Robust Principal Component Analysis (TRPCA) and a Two-Stream Composed of Visual Geometry Group Network (VGG) and Bi-Long Short-Term Memory (BLSTM) (TSVB) model is proposed for forest fire smoke detection, showing strong robustness against interference factors in a complex background.
Book ChapterDOI
Early Smoke Detection in Outdoor Space by Spatio-Temporal Clustering Using a Single Video Camera
TL;DR: Experimental results show that the proposed set of spatial and temporal features well discriminates smoke and non-smoke regions in outdoor scenes with a complex background.
Proceedings ArticleDOI
Smoke Recognition Based on Machine Vision
TL;DR: Vision-based smoke detection approach using image processing technology in smart monitoring system is proposed for early alarm and it is shown that it is feasible and effective and has strong robustness and high real time.
Journal ArticleDOI
Fusing texture, edge and line features for smoke recognition
TL;DR: The Canny operator is proposed to generate an edge image from an original image, and then adopt the Hough transform to extract straight lines from the edge image, which outperforms most of existing traditional methods for smoke recognition.
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.