3D Human motion tracking by exemplar-based conditional particle filter

This method retains advantages of classic particle filters while increases prediction accuracy by replacing the smooth motion model with exemplars-based dynamic model which constrains evolved particles within an area closer to true state. Therefore, tracking robustness to discontinuous motion is improved such as under conditions of sudden change in motion velocity or using low-frame rate cameras. To verify the effectiveness and efficiency of the proposed algorithm, a variety of datasets are selected for testing and the results are also compared with the state-of-the-art methods in this domain.