IEEE Trans Image Process - Optical flow estimation for flame detection in videos.

Tópicos

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Resumo

Computational vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. Whereas many discriminating features, such as color, shape, texture, etc., have been employed in the literature, this paper proposes a set of motion features based on motion estimators. The key idea consists of exploiting the difference between the turbulent, fast, fire motion, and the structured, rigid motion of other objects. Since classical optical flow methods do not model the characteristics of fire motion (e.g., non-smoothness of motion, non-constancy of intensity), two optical flow methods are specifically designed for the fire detection task: optimal mass transport models fire with dynamic texture, while a data-driven optical flow scheme models saturated flames. Then, characteristic features related to the flow magnitudes and directions are computed from the flow fields to discriminate between fire and non-fire motion. The proposed features are tested on a large video database to demonstrate their practical usefulness. Moreover, a novel evaluation method is proposed by fire simulations that allow for a controlled environment to analyze parameter influences, such as flame saturation, spatial resolution, frame rate, and random noise.

Resumo Limpo

comput visionbas flame detect drawn signific attent past decad camera surveil system becom ubiquit wherea mani discrimin featur color shape textur etc employ literatur paper propos set motion featur base motion estim key idea consist exploit differ turbul fast fire motion structur rigid motion object sinc classic optic flow method model characterist fire motion eg nonsmooth motion nonconst intens two optic flow method specif design fire detect task optim mass transport model fire dynam textur datadriven optic flow scheme model satur flame characterist featur relat flow magnitud direct comput flow field discrimin fire nonfir motion propos featur test larg video databas demonstr practic use moreov novel evalu method propos fire simul allow control environ analyz paramet influenc flame satur spatial resolut frame rate random nois

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