Video Flame Detection Method Based on TwoStream Convolutional Neural Network

Flame detection based on computer vision is one of the key technologies of the modern surveillance system. However, how to reliably and accurately detect the flame is still a tricky problem. In this paper, a video flame detection method based on two-stream convolutional neural network combining spatial and temporal features is proposed. Firstly, the suspected flame region is extracted from the video by the combination of motion feature detection and color feature detection. Next, and the extracted suspected region is classified by the two-stream convolutional neural network. Finally, the region whose classification result is flame is output as the final detection result. The experimental results on the collected flame data set show that the proposed flame detection method can effectively improve the detection accuracy.