期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：4
DOI：10.15680/ijircce.2015.0304065
出版社：S&S Publications
摘要：Detecting fire break out is absolutely necessary in order to prevent loss of life and property. The vision –based fire detection techniques with surveillance systems have become popular in the past decade. Video camera coverswide viewing range and from the data captured by video camera additional information can be extracted. Videosequences provide an insightful view about how the object and scenes in the video change over time. For indoor firedetection, traditional point sensors were used to detect heat or smoke particles. However, when it comes to open spaceit is not viable to employ these point sensors. Optical flow estimators transform the image sequence into estimatedmotion. Optical flow vector is created in the system and is used to depict the magnitude and direction of motion of anobject as it moves from one frame to another. Based on the motion estimators, a set of motion features is presented thatexploits the difference between dynamic fire motion and rigid fire motion. Two optical flow methods are designed forflame flow vector creation, namely, Non-Smooth Data (NSD) and Optimal Mass Transport (OMT). NSD and OMTmethods are used for modelling flame with dynamic texture and saturated fire blob respectively. To further enhance theprocess of flame detection, gradient optical flow estimation methods and classification based on feature vectors have tobe done
关键词：Fire detection; flow vector; gradient estimation; optical flow; optimal mass transport; non-smooth data
