## 基于GPU加速的OpenCV人體檢測（Full Body Detection） ### 1、CUDA和OpenCV的安裝 首先，確定一下自己的平臺是否安裝好了CUDA和OpenCV。 CUDA的安裝可以參考：[http://blog.csdn.net/frd2009041510/article/details/42042807](http://blog.csdn.net/frd2009041510/article/details/42042807)和[http://blog.csdn.net/frd2009041510/article/details/42925205](http://blog.csdn.net/frd2009041510/article/details/42925205) OpenCV的安裝可以參考：[http://blog.csdn.net/frd2009041510/article/details/42930113](http://blog.csdn.net/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 ~~~ 進入目錄：  編譯：  ### 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. 結果截圖如下：   如果有攝像頭，可以執行下面的命令來完成演示： ~~~ ./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! 結果截圖如下：  ### 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!**