Target tracking based on feature fusion of visible and infrared image

Aiming at the problem that the accuracy of tracking object is not high when with a single image source,CAMShift(Continuously Adaptive Mean Shift) tracking algorithm is improved by using different characteristics of the tracked target in the visible images and infrared images.Firstly,"color-gradient back projection" is selected as the improved target model in visible image,and "gray-gradient back projection" is selected as the improved target model in infrared image.Then the coefficient of qiwhich is got by using the improved CAM Shift tracking algorithm in visible images and infrared images respectively is used to judge the effect of the two images tracking.The weights of two images are adjusted adaptively by the coefficient of qi.Finally,the feature fusion image and the location of object are got according to the respective weight.The experimental results show that,for visible and infrared image of 320pixel×240pixel,the object tracking algorithm which is based on feature fusion by visible images and infrared images can get much accurate location of tracking target under complex background in which the accuracy of tracking object is 0.5pixel,and the velocity of tracking object is 30-32 ms/frame.