def METHOD_NAME(self, new_track_state):
    if not self.track_state_list:
        new_track_state.motion_feature = torch.FloatTensor(2).zero_()
    else:
        pre_bbox_center = np.asarray(self.track_state_list[-1].bbox_center, dtype=np.float32).reshape(2)
        cur_bbox_center = np.asarray(new_track_state.bbox_center, dtype=np.float32).reshape(2)
        new_track_state.motion_feature = torch.from_numpy(cur_bbox_center - pre_bbox_center)
    new_track_state.track_id = self.track_id
    self.track_state_list.METHOD_NAME(new_track_state)
    self.max_conf = max(self.max_conf, new_track_state.conf)