【姿态检测】win10+Azure Kinect Dk 人体姿态跟踪使用教程

由于项目需要，使用了Azure Kinect DK的深度相机设备，由于内含人体姿态检测的SDK，所以拿来玩一玩

设备文档介绍：https://docs.microsoft.com/zh-cn/azure/Kinect-dk/set-up-azure-kinect-dk

一、设备连接

硬件部分的连接示意图如下：

1、将电源连接器插入设备背面的电源插孔。将 USB 电源适配器连接到线缆的另一端，然后将适配器插入电源插座；

2、将 USB 数据线的一端连接到设备，将另一端连接到电脑上的 USB 3.0 端口(这里我遇到一些问题，驱动始终无法识别，经过查找网上经验吗，将其连接到距离主板最近的那个USB口，才可以连接成功)

3、验证电源指示器 LED（USB 电缆旁边）是否为纯白。

4、系统要求：官网中的系统要求是Windows10或者ubuntu18.04的操作系统

网上的经验说Ubuntu16.04也可以，不过我直接用了win10的系统。

二、下载SDK

SDK下载地址：https://docs.microsoft.com/zh-cn/azure/Kinect-dk/sensor-sdk-download

也可以在GitHub源码中找到其他版本下载

源码：https://github.com/microsoft/Azure-Kinect-Sensor-SDK

SDK版本：https://github.com/microsoft/Azure-Kinect-Sensor-SDK/blob/develop/docs/usage.md

三、检查设备连接成功

启动 Azure Kinect 查看器：双击文件中的执行文件 C:\Program Files\Azure Kinect SDK vX.Y.Z\tools\k4aviewer.exe，其中的 X.Y.Z 是安装的 SDK版本，可以看到如下图：

这里会自动搜索到相机，如果没搜索到，说明驱动安装失败，还是要连接到距离主板最近的那个USB口，并且USB口需要时USB3.0版本，选择相机的配置选项后，点击start就可以看到效果：

进入 C:\Program Files\Azure Kinect Body Tracking SDK\tools\文件夹中，有一个k4abt_simple_3d_viewer可执行文件，可以在Powershell中运行。命令是：./k4abt_simple_3d_viewer.exe CPU，如果没有使用CUDA，可在后面加CPU，表示用CPU运行

四、SDK的使用

相机函数调用：https://docs.microsoft.com/zh-cn/azure/Kinect-dk/build-first-app

人体姿态识别函数调用：https://docs.microsoft.com/zh-cn/azure/Kinect-dk/build-first-body-app

安装opencv3

下载VS2019 ，并新建一个C++ windows 控制台的项目，然后需要拷贝一些SDK内容以及相关库过来：

将Azure Kinect SDK v1.3.0\sdk\include\中的k4a.h、k4a.hpp、k4a_export.h、k4atypes.h、k4aversion.h拷贝到项目文件夹下的include文件夹下
将Azure Kinect Body Tracking SDK\sdk\include中的k4abt.h、k4abt.hpp、k4abttypes.h、k4abtversion.h拷贝到项目文件夹下的include文件夹下
将opencv\build\include\opencv2中的core.hpp、opencv.hpp、opencv_modules.hpp拷贝到项目文件夹下的include文件夹下
将opencv\build\include\opencv2文件夹直接拷贝到项目wen'文件夹下
将Azure Kinect SDK v1.3.0\tools文件夹下的depthengine_2_0.dll、k4a.dll拷贝到项目文件夹下
将Azure Kinect Body Tracking SDK\tools文件夹下的cublas64_100.dll、cudart64_100.dll、cudnn64_7.dll、dnn_model_2_0.onnx拷贝到项目文件夹下

接下来就可以写自己的主函数了

k4abttypes.h的函数中设置使用CPU还是GPUwo'd

typedef enum
{K4ABT_TRACKER_PROCESSING_MODE_GPU = 0, /**< SDK will use GPU mode to run the tracker */K4ABT_TRACKER_PROCESSING_MODE_CPU,     /**< SDK will use CPU only mode to run the tracker */
} k4abt_tracker_processing_mode_t;

我的主程序，主要是展示关节点坐标，及一些关键点的关系

#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#include "include/k4a.h"
#include "include/k4abt.h"
#include <math.h>// OpenCV
#include "include/opencv.hpp"
// Kinect DK
#include "include/k4a.hpp"#define VERIFY(result, error)                                                                            \if(result != K4A_RESULT_SUCCEEDED)                                                                   \{                                                                                                    \printf("%s \n - (File: %s, Function: %s, Line: %d)\n", error, __FILE__, __FUNCTION__, __LINE__); \exit(1);                                                                                         \}                                                                                                    \int main()
{//定义身高float UPPER_BODY; //上身长度float body_angel; //上身倾角k4a_device_t device = NULL;VERIFY(k4a_device_open(0, &device), "Open K4A Device failed!");const uint32_t device_count = k4a_device_get_installed_count();if (1 == device_count){std::cout << "Found " << device_count << " connected devices. " << std::endl;}else{std::cout << "Error: more than one K4A devices found. " << std::endl;}//打开设备k4a_device_open(0, &device);std::cout << "Done: open device. " << std::endl;// Start camera. Make sure depth camera is enabled.k4a_device_configuration_t deviceConfig = K4A_DEVICE_CONFIG_INIT_DISABLE_ALL;deviceConfig.depth_mode = K4A_DEPTH_MODE_NFOV_2X2BINNED;deviceConfig.color_resolution = K4A_COLOR_RESOLUTION_720P;deviceConfig.camera_fps = K4A_FRAMES_PER_SECOND_30;deviceConfig.color_format = K4A_IMAGE_FORMAT_COLOR_BGRA32;deviceConfig.synchronized_images_only = true;// ensures that depth and color images are both available in the capture//开始相机//k4a_device_start_cameras(device, &deviceConfig);VERIFY(k4a_device_start_cameras(device, &deviceConfig), "Start K4A cameras failed!");std::cout << "Done: start camera." << std::endl;//查询传感器校准k4a_calibration_t sensor_calibration;k4a_device_get_calibration(device, deviceConfig.depth_mode, deviceConfig.color_resolution, &sensor_calibration);VERIFY(k4a_device_get_calibration(device, deviceConfig.depth_mode, deviceConfig.color_resolution, &sensor_calibration),"Get depth camera calibration failed!");//创建人体跟踪器k4abt_tracker_t tracker = NULL;k4abt_tracker_configuration_t tracker_config = K4ABT_TRACKER_CONFIG_DEFAULT;k4abt_tracker_create(&sensor_calibration, tracker_config, &tracker);VERIFY(k4abt_tracker_create(&sensor_calibration, tracker_config, &tracker), "Body tracker initialization failed!");cv::Mat cv_rgbImage_with_alpha;cv::Mat cv_rgbImage_no_alpha;cv::Mat cv_depth;cv::Mat cv_depth_8U;int frame_count = 0;while(true){k4a_capture_t sensor_capture;k4a_wait_result_t get_capture_result = k4a_device_get_capture(device, &sensor_capture, K4A_WAIT_INFINITE);//获取RGB和depth图像k4a_image_t rgbImage = k4a_capture_get_color_image(sensor_capture);k4a_image_t depthImage = k4a_capture_get_depth_image(sensor_capture);//RGBcv_rgbImage_with_alpha = cv::Mat(k4a_image_get_height_pixels(rgbImage), k4a_image_get_width_pixels(rgbImage), CV_8UC4, k4a_image_get_buffer(rgbImage));cvtColor(cv_rgbImage_with_alpha, cv_rgbImage_no_alpha, cv::COLOR_BGRA2BGR);      //depthcv_depth = cv::Mat(k4a_image_get_height_pixels(depthImage), k4a_image_get_width_pixels(depthImage), CV_16U, k4a_image_get_buffer(depthImage), k4a_image_get_stride_bytes(depthImage));cv_depth.convertTo(cv_depth_8U, CV_8U, 1);//计算姿态if (get_capture_result == K4A_WAIT_RESULT_SUCCEEDED){frame_count++;k4a_wait_result_t queue_capture_result = k4abt_tracker_enqueue_capture(tracker, sensor_capture, K4A_WAIT_INFINITE);k4a_capture_release(sensor_capture); // Remember to release the sensor capture once you finish using itif (queue_capture_result == K4A_WAIT_RESULT_TIMEOUT){// It should never hit timeout when K4A_WAIT_INFINITE is set.printf("Error! Add capture to tracker process queue timeout!\n");break;}else if (queue_capture_result == K4A_WAIT_RESULT_FAILED){printf("Error! Add capture to tracker process queue failed!\n");break;}k4abt_frame_t body_frame = NULL;k4a_wait_result_t pop_frame_result = k4abt_tracker_pop_result(tracker, &body_frame, K4A_WAIT_INFINITE);if (pop_frame_result == K4A_WAIT_RESULT_SUCCEEDED){// Successfully popped the body tracking result. Start your processing size_t num_bodies = k4abt_frame_get_num_bodies(body_frame);for (size_t i = 0; i < num_bodies; i++){k4abt_skeleton_t skeleton;k4abt_frame_get_body_skeleton(body_frame, i, &skeleton);//std::cout << typeid(skeleton.joints->position.v).name();k4a_float2_t P_HEAD_2D;k4a_float2_t P_NECK_2D;k4a_float2_t P_CHEST_2D;k4a_float2_t P_HIP_2D;k4a_float2_t P_CLAVICLE_RIGHT_2D;k4a_float2_t P_CLAVICLE_LEFT_2D;k4a_float2_t P_HIP_RIGHT_2D;k4a_float2_t P_HIP_LEFT_2D;k4a_float2_t P_KNEE_LEFT_2D;k4a_float2_t P_KNEE_RIGHT_2D;int result;//头部k4abt_joint_t  P_HEAD = skeleton.joints[K4ABT_JOINT_NOSE];//3D转2D，并在color中画出k4a_calibration_3d_to_2d(&sensor_calibration, &P_HEAD.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_HEAD_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_HEAD_2D.xy.x, P_HEAD_2D.xy.y), 3, cv::Scalar(0, 255, 255));//颈部k4abt_joint_t  P_NECK = skeleton.joints[K4ABT_JOINT_NECK];//3D转2D，并在color中画出k4a_calibration_3d_to_2d(&sensor_calibration, &P_NECK.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_CHEST_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_CHEST_2D.xy.x, P_CHEST_2D.xy.y), 3, cv::Scalar(0, 255, 255));//胸部k4abt_joint_t  P_CHEST = skeleton.joints[K4ABT_JOINT_SPINE_CHEST];//3D转2D，并在color中画出k4a_calibration_3d_to_2d(&sensor_calibration, &P_CHEST.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_NECK_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_NECK_2D.xy.x, P_NECK_2D.xy.y), 3, cv::Scalar(0, 255, 255));//髋部k4abt_joint_t  P_HIP = skeleton.joints[K4ABT_JOINT_PELVIS];//3D转2D，并在color中画出k4a_calibration_3d_to_2d(&sensor_calibration, &P_HIP.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_HIP_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_HIP_2D.xy.x, P_HIP_2D.xy.y), 3, cv::Scalar(0, 255, 255));//右肩（计算上身倾角需要）k4abt_joint_t  P_CLAVICLE_RIGHT = skeleton.joints[K4ABT_JOINT_CLAVICLE_RIGHT];//3D转2D，并在color中画出k4a_calibration_3d_to_2d(&sensor_calibration, &P_CLAVICLE_RIGHT.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_CLAVICLE_RIGHT_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_CLAVICLE_RIGHT_2D.xy.x, P_CLAVICLE_RIGHT_2D.xy.y), 3, cv::Scalar(0, 255, 255));//右髋（计算上身倾角需要）k4abt_joint_t  P_HIP_RIGHT = skeleton.joints[K4ABT_JOINT_HIP_RIGHT];//3D转2D，并在color中画出,并画出右肩到右髋的连线k4a_calibration_3d_to_2d(&sensor_calibration, &P_HIP_RIGHT.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_HIP_RIGHT_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_HIP_RIGHT_2D.xy.x, P_HIP_RIGHT_2D.xy.y), 3, cv::Scalar(0, 255, 255));cv::line(cv_rgbImage_no_alpha, cv::Point(P_CLAVICLE_RIGHT_2D.xy.x, P_CLAVICLE_RIGHT_2D.xy.y), cv::Point(P_HIP_RIGHT_2D.xy.x, P_HIP_RIGHT_2D.xy.y), cv::Scalar(0, 0, 255), 2);//右膝（计算上身倾角需要）k4abt_joint_t  P_KNEE_RIGHT = skeleton.joints[K4ABT_JOINT_KNEE_RIGHT];//3D转2D，并在color中画出,并画出右肩到右膝、右髋到右膝的连线k4a_calibration_3d_to_2d(&sensor_calibration, &P_KNEE_RIGHT.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_KNEE_RIGHT_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_KNEE_RIGHT_2D.xy.x, P_KNEE_RIGHT_2D.xy.y), 3, cv::Scalar(0, 255, 255));cv::line(cv_rgbImage_no_alpha, cv::Point(P_CLAVICLE_RIGHT_2D.xy.x, P_CLAVICLE_RIGHT_2D.xy.y), cv::Point(P_KNEE_RIGHT_2D.xy.x, P_KNEE_RIGHT_2D.xy.y), cv::Scalar(0, 0, 255), 2);cv::line(cv_rgbImage_no_alpha, cv::Point(P_HIP_RIGHT_2D.xy.x, P_HIP_RIGHT_2D.xy.y), cv::Point(P_KNEE_RIGHT_2D.xy.x, P_KNEE_RIGHT_2D.xy.y), cv::Scalar(0, 0, 255), 2);//左肩（计算上身倾角需要）k4abt_joint_t  P_CLAVICLE_LEFT = skeleton.joints[K4ABT_JOINT_CLAVICLE_LEFT];//3D转2D，并在color中画出k4a_calibration_3d_to_2d(&sensor_calibration, &P_CLAVICLE_LEFT.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_CLAVICLE_LEFT_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_CLAVICLE_LEFT_2D.xy.x, P_CLAVICLE_LEFT_2D.xy.y), 3, cv::Scalar(0, 255, 255));//左髋（计算上身倾角需要）k4abt_joint_t  P_HIP_LEFT = skeleton.joints[K4ABT_JOINT_HIP_LEFT];//3D转2D，并在color中画出,并画出左肩到左髋的连线k4a_calibration_3d_to_2d(&sensor_calibration, &P_HIP_LEFT.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_HIP_LEFT_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_HIP_LEFT_2D.xy.x, P_HIP_LEFT_2D.xy.y), 3, cv::Scalar(0, 255, 255));cv::line(cv_rgbImage_no_alpha, cv::Point(P_HIP_LEFT_2D.xy.x, P_HIP_LEFT_2D.xy.y), cv::Point(P_CLAVICLE_LEFT_2D.xy.x, P_CLAVICLE_LEFT_2D.xy.y), cv::Scalar(0, 0, 255), 2);//左膝（计算上身倾角需要）k4abt_joint_t  P_KNEE_LEFT = skeleton.joints[K4ABT_JOINT_KNEE_LEFT];//3D转2D，并在color中画出,并画出左肩到左膝、左髋到左膝的连线k4a_calibration_3d_to_2d(&sensor_calibration, &P_KNEE_LEFT.position, K4A_CALIBRATION_TYPE_DEPTH, K4A_CALIBRATION_TYPE_COLOR, &P_KNEE_LEFT_2D, &result);cv::circle(cv_rgbImage_no_alpha, cv::Point(P_KNEE_LEFT_2D.xy.x, P_KNEE_LEFT_2D.xy.y), 3, cv::Scalar(0, 255, 255));cv::line(cv_rgbImage_no_alpha, cv::Point(P_CLAVICLE_LEFT_2D.xy.x, P_CLAVICLE_LEFT_2D.xy.y), cv::Point(P_KNEE_LEFT_2D.xy.x, P_KNEE_LEFT_2D.xy.y), cv::Scalar(0, 0, 255), 2);cv::line(cv_rgbImage_no_alpha, cv::Point(P_HIP_LEFT_2D.xy.x, P_HIP_LEFT_2D.xy.y), cv::Point(P_KNEE_LEFT_2D.xy.x, P_KNEE_LEFT_2D.xy.y), cv::Scalar(0, 0, 255), 2);//输出头部关键点坐标（skeleton.joints_HEAD->position.v为头部坐标点，数据结构float[3]）char text_head[50];std::cout << "头部坐标：";for (size_t i = 0; i < 3; i++){std::cout << P_HEAD.position.v[i] << " ";}printf("\n");//输出颈部关键点坐标std::cout << "颈部坐标：";for (size_t i = 0; i < 3; i++){std::cout << P_NECK.position.v[i] << " " ;}printf("\n");//输出胸部关键点坐标std::cout << "胸部坐标：";for (size_t i = 0; i < 3; i++){std::cout << P_CHEST.position.v[i] << " ";}printf("\n");//输出髋部关键点坐标std::cout << "髋部坐标：";for (size_t i = 0; i < 3; i++){std::cout << P_HIP.position.v[i] << " ";}printf("\n");//估算人体身高UPPER_BODY= sqrt(pow((P_NECK.position.xyz.x - P_HIP.position.xyz.x),2) +pow((P_NECK.position.xyz.y - P_HIP.position.xyz.y),2) + pow((P_NECK.position.xyz.z - P_HIP.position.xyz.z),2));float HEIGHT = UPPER_BODY  * 1770/518;std::cout << "估算身高高度是;" << HEIGHT << std::endl;//估算上身倾角float ang_clavicetohip_right = sqrt(pow((P_CLAVICLE_RIGHT.position.xyz.x - P_HIP_RIGHT.position.xyz.x), 2) + pow((P_CLAVICLE_RIGHT.position.xyz.y - P_HIP_RIGHT.position.xyz.y), 2) + pow((P_CLAVICLE_RIGHT.position.xyz.z - P_HIP_RIGHT.position.xyz.z), 2));float ang_clavicetohip_left = sqrt(pow((P_CLAVICLE_LEFT.position.xyz.x - P_HIP_LEFT.position.xyz.x), 2) + pow((P_CLAVICLE_LEFT.position.xyz.y - P_HIP_LEFT.position.xyz.y), 2) + pow((P_CLAVICLE_LEFT.position.xyz.z - P_HIP_LEFT.position.xyz.z), 2));float ang_hiptoknee_right = sqrt(pow((P_HIP_RIGHT.position.xyz.x - P_KNEE_RIGHT.position.xyz.x), 2) + pow((P_HIP_RIGHT.position.xyz.y - P_KNEE_RIGHT.position.xyz.y), 2) + pow((P_HIP_RIGHT.position.xyz.z - P_KNEE_RIGHT.position.xyz.z), 2));float ang_hiptoknee_left = sqrt(pow((P_HIP_LEFT.position.xyz.x - P_KNEE_LEFT.position.xyz.x), 2) + pow((P_HIP_LEFT.position.xyz.y - P_KNEE_LEFT.position.xyz.y), 2) + pow((P_HIP_LEFT.position.xyz.z - P_KNEE_LEFT.position.xyz.z), 2));float ang_clavicetoknee_right = sqrt(pow((P_CLAVICLE_RIGHT.position.xyz.x - P_KNEE_RIGHT.position.xyz.x), 2) + pow((P_CLAVICLE_RIGHT.position.xyz.y - P_KNEE_RIGHT.position.xyz.y), 2) + pow((P_CLAVICLE_RIGHT.position.xyz.z - P_KNEE_RIGHT.position.xyz.z), 2));float ang_clavicetoknee_left = sqrt(pow((P_CLAVICLE_LEFT.position.xyz.x - P_KNEE_LEFT.position.xyz.x), 2) + pow((P_CLAVICLE_LEFT.position.xyz.y - P_KNEE_LEFT.position.xyz.y), 2) + pow((P_CLAVICLE_LEFT.position.xyz.z - P_KNEE_LEFT.position.xyz.z), 2));float body_angel_right = acos((ang_clavicetohip_right * ang_clavicetohip_right + ang_hiptoknee_right * ang_hiptoknee_right - ang_clavicetoknee_right * ang_clavicetoknee_right) / (2 * ang_clavicetohip_right * ang_hiptoknee_right)) * 180.0 / 3.1415926;float body_angel_left = acos((ang_clavicetohip_left * ang_clavicetohip_left + ang_hiptoknee_left * ang_hiptoknee_left - ang_clavicetoknee_left * ang_clavicetoknee_left) / (2 * ang_clavicetohip_left * ang_hiptoknee_left)) * 180.0 / 3.1415926;body_angel = (body_angel_right + body_angel_left)/2;std::cout << "估算上身倾角是;" << body_angel << std::endl;uint32_t id = k4abt_frame_get_body_id(body_frame, i);}printf("%zu bodies are detected!\n", num_bodies);k4abt_frame_release(body_frame); // Remember to release the body frame once you finish using it}else if (pop_frame_result == K4A_WAIT_RESULT_TIMEOUT){//  It should never hit timeout when K4A_WAIT_INFINITE is set.printf("Error! Pop body frame result timeout!\n");break;}else{printf("Pop body frame result failed!\n");break;}}else if (get_capture_result == K4A_WAIT_RESULT_TIMEOUT){// It should never hit time out when K4A_WAIT_INFINITE is set.printf("Error! Get depth frame time out!\n");break;}else{printf("Get depth capture returned error: %d\n", get_capture_result);break;}// show imageimshow("color", cv_rgbImage_no_alpha);imshow("depth", cv_depth_8U);cv::waitKey(0);k4a_image_release(rgbImage);}printf("Finished body tracking processing!\n");k4abt_tracker_shutdown(tracker);k4abt_tracker_destroy(tracker);k4a_device_stop_cameras(device);k4a_device_close(device);return 0;
}