NVIDIA Jetson TK1学习与开发（九）：基于GPU加速的OpenCV人体检测（Full Body Detection）

基于GPU加速的OpenCV人体检测（Full Body Detection）

1、CUDA和OpenCV的安装

首先，确定一下自己的平台是否安装好了CUDA和OpenCV。

CUDA的安装可以参考：http://blog.youkuaiyun.com/frd2009041510/article/details/42042807和http://blog.youkuaiyun.com/frd2009041510/article/details/42925205

OpenCV的安装可以参考：http://blog.youkuaiyun.com/frd2009041510/article/details/42930113

2、Simply build the OpenCV HOG (Hough Of Gradients) sample person detector program

cd opencv-2.4.9/samples/gpu
g++ hog.cpp -lopencv_core -lopencv_imgproc -lopencv_highgui -lopencv_calib3d -lopencv_contrib -lopencv_features2d -lopencv_flann -lopencv_gpu -lopencv_legacy -lopencv_ml -lopencv_nonfree -lopencv_objdetect -lopencv_photo -lopencv_stitching -lopencv_superres -lopencv_video -lopencv_videostab -o hog

进入目录：

编译：

3、run the HOG demo

./hog --video 768x576.avi

注意：You can run the HOG demo such as on a pre-recorded video of people walking around. The HOG demo displays a graphical output, hence you should plug a HDMI monitor in or use a remote viewer such as X Tunneling or VNC or TeamViewer on your desktop in order to see the output.

结果截图如下：

如果有摄像头，可以执行下面的命令来完成演示：

./hog --camera 0

注意：Note: This looks for whole bodies and assumes they are small, so you need to stand atleast 5m away from the camera if you want it to detect you!

结果截图如下：

4、HOG demo中的一些控制命令

You can toggle between CPU vs GPU by pressing 'm', where you will see that the GPU is typically 5x faster at HOG than the CPU!