关键词: 粒子滤波, Mean Shift, 火焰识别, 火焰跟踪

Abstract: Hybrid particle filter based flame tracking algorithm is proposed in this paper.In order to decrease the computational load of general particle filter,Mean Shift algorithm is embedded into particle filter.At the same time a new adaptive state transition model and an auto-updating strategy of object model are used to improve the performance of hybrid particle filter algorithm.Then,a flame tracking algorithm composed of flame detection and flame tracking is presented.The first phase is flame recognition and the next is flame tracking.If the likelihood of a candidate with the model is smaller than a threshold,it would get into the first phase during tracking.Auto-switch between detection and tracking ensures the validity of flame tracking.The experiment results show that the hybrid particle filter has a good performance.Compared with Mean Shift and general particle filter,it improves the tracking precision.Hybrid particle filter based flame tracking method can track the moving flame under the complex actual environment and get the flame position information.

Key words: particle filter, Mean Shift, flame detection, flame tracking