Detection and tracking of multiple moving objects in video sequence using entropy mask method and fast level set method

In this paper, we propose a novel algorithm for real-time detection and tracking of multiple moving objects, which sequentially integrates the entropy difference method with adaptive threshold and the fast level set method. First, we have applied the Clausius Entropy theory to convert the pixel value in image domain into the amount of energy change in entropy domain. And then we apply the entropy difference detection method to detect the coarse region of the moving objects in this image and we have constructed the mask covering a detected coarse region. Second, taking the initial value of the level set for moving object as the constructed mask region, we have applied the fast level set technique to track rapidly the contour of detected objects. Here, we have used the fast level set method that combines the Fast Marching Method and the Smart Narrow Band. Experiment results demonstrate that our method can detect and track effectively and accurately the motion objects in video sequence.