def METHOD_NAME(pre_gray, cur_gray, prev_cfd, dl_weights,
                              disflow):
    """计算光流跟踪匹配点和光流图
    输入参数:
        pre_gray: 上一帧灰度图
        cur_gray: 当前帧灰度图
        prev_cfd: 上一帧光流图
        dl_weights: 融合权重图
        disflow: 光流数据结构
    返回值:
        is_track: 光流点跟踪二值图，即是否具有光流点匹配
        track_cfd: 光流跟踪图
    """
    check_thres = 8
    h, w = pre_gray.shape[:2]
    track_cfd = np.zeros_like(prev_cfd)
    is_track = np.zeros_like(pre_gray)
    flow_fw = disflow.calc(pre_gray, cur_gray, None)
    flow_bw = disflow.calc(cur_gray, pre_gray, None)
    flow_fw = np.round(flow_fw).astype(np.int)
    flow_bw = np.round(flow_bw).astype(np.int)
    y_list = np.array(range(h))
    x_list = np.array(range(w))
    yv, xv = np.meshgrid(y_list, x_list)
    yv, xv = yv.T, xv.T
    cur_x = xv + flow_fw[:, :, 0]
    cur_y = yv + flow_fw[:, :, 1]
    # 超出边界不跟踪
    not_track = (cur_x < 0) + (cur_x >= w) + (cur_y < 0) + (cur_y >= h)
    flow_bw[~not_track] = flow_bw[cur_y[~not_track], cur_x[~not_track]]
    not_track += (np.square(flow_fw[:, :, 0] + flow_bw[:, :, 0]) +
                  np.square(flow_fw[:, :, 1] + flow_bw[:, :, 1])
                  ) >= check_thres
    track_cfd[cur_y[~not_track], cur_x[~not_track]] = prev_cfd[~not_track]
    is_track[cur_y[~not_track], cur_x[~not_track]] = 1
    not_flow = np.all(np.abs(flow_fw) == 0,
                      axis=-1) * np.all(np.abs(flow_bw) == 0, axis=-1)
    dl_weights[cur_y[not_flow], cur_x[not_flow]] = 0.05
    return track_cfd, is_track, dl_weights