文件名称:kalman
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2015-04-16
- 文件大小：
- 27.6mb
- 下载次数：
- 0次
- 提 供 者：
- xiaor******
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
分为行人检测，特征提取，行人跟踪三步，其中最主要的代码也是这个代码的中心是行人跟踪这一部分，我采用的是kalman滤波器进行行人下一帧位置的预测，可以很好的提高行人跟踪的鲁棒性，跟踪结果比较准确。-Into pedestrian detection, feature extraction, pedestrian tracking steps, which is the center of the main code of the code is pedestrian tracking this section, I kalman filter is used to predict the position of the next fr a me pedestrians, can be a good improvement pedestrian tracking robustness, tracking results more accurate.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
kalman滤波实现视频目标跟踪
..........................\1.avi
..........................\AR_to_SS.m
..........................\convert_to_lagged_form 递归.m
..........................\ensure_AR.m
..........................\eval_AR_perf.m
..........................\extract.m
..........................\gaussian_prob.m
..........................\hs_err_pid3492.log
..........................\kalman.asv
..........................\kalman.m
..........................\kalman_filter 卡尔曼滤波器.m
..........................\kalman_forward_backward.m
..........................\kalman_smoother.m
..........................\kalman_update.asv
..........................\kalman_update.m
..........................\learning_demo.m
..........................\learn_AR.m
..........................\learn_AR_diagonal.m
..........................\learn_kalman.m
..........................\plotcov2.m
..........................\plotgauss2d.m
..........................\plot_ellipse.m
..........................\process_options.m
..........................\README
..........................\README.txt
..........................\README.txt~
..........................\SampleVideo.avi
..........................\SampleVideo1.avi
..........................\sample_gaussian.m
..........................\sample_lds.asv
..........................\sample_lds.m
..........................\smooth_update.m
..........................\SS_to_AR.m
..........................\testKalman.m
..........................\tracking_demo.m
..........................\说明.txt