The analysis of cell and pathogen movement and motility is a major topic in cell biology for which computerized methods are most needed. This study proposes a method to detect and track multiple moving biological objects in image sequences acquired through fluorescence video microscopy. The method enables the analysis of video microscopy image sequences in order to obtain reliable quantitative data such as number, position, speed and movement phases. The method consists of three stages. A stage of detection is performed through a multi-scale analysis of images using an undecimated wavelet transform. The next stage is the prediction of the state of each detected spot in the next frame using a Kalman filter and an adapted model. Then comes a stage of data association which constructs the tracks and refines the filters. Once all moving objects have been assigned with unique spatio-temporal paths, trajectories are analyzed in terms of different parameters relevant to the motility analysis of biological objects.