An object tracking algorithm based on adaptive particle filter is proposed in this paper. Boosting algorithm is introduced into particle filter algorithm

and adaptive particle filter is constructed. Features classifiers are constructed utilizing object information and background information

and the outputs of these classifiers taken as important information of observations of particle filter are used to calculate particles’ coefficient. Also

these classifiers are updated during tracking in order to update particles’ coefficient adaptively. The experiment result shows that the tracking algorithm we proposed can adaptively select features for tracking utilizing different background information

in applications such as existence of covering

appearance changed

clutter in the background and illumination changing. The objects can be tracked stably.