Affectiva 可以连接 Kinect v1 吗?

我有一个在 Ubuntu 14.04 上提供免费的情感识别版本的 Affectivahttps://developer.affectiva.com/的项目。 我正在尝试使用 Kinect v1 作为 Affectiva 的输入设备。 我使用 lsusb 查找 kinect v1 的 ID 是巴士 003 设备 009： ID 045e：02ae Microsoft 公司 Xbox 努伊相机 .我尝试在affdex-sdk/CameraDetector.h和build/opencv-webcam-demo上修改const int cameraId = 045e：02ae。

#pragma once
#include <memory>
#include "FrameDetector.h"
namespace affdex
{
// Forward Declarations
class Camera;
/// <summary>
/// A detector used to acquire and process frames from a physical camera.
/// </summary>
class CameraDetector : public FrameDetector
{
public:
/// <summary>
/// Creates a CameraDetector.
/// This class acquires the device camera and will immediately start processing frames from the camera feed.
/// Processing is asynchronous so some frames may be dropped.
/// <param name="cameraId">Device id for the camera. </param>
/// <param name="cameraFPS">Capture framerate from the camera. Must be positive.</param>
/// <param name="processFPS">Maximum framerate from processing. Must be positive.</param>
/// <param name="maxNumFaces">The max number of faces to be tracked.</param>
/// <param name="faceConfig">Maximum processing framerate.</param>
/// </summary>
AFFDEXSDK CameraDetector(const int cameraId = 045e:02ae, const double cameraFPS =20 ,
const double processFPS = DEFAULT_PROCESSING_FRAMERATE,
const unsigned int maxNumFaces = DEFAULT_MAX_NUM_FACES,
const FaceDetectorMode faceConfig = affdex::FaceDetectorMode::LARGE_FACES);
/// <summary>
/// Finalizes an instance of the <see cref="CameraDetector"/> class.
/// </summary>
AFFDEXSDK virtual ~CameraDetector() override;
/// <summary>
/// Initializes the CameraDetector and starts producing frames and results immediately.
/// </summary>
AFFDEXSDK virtual void start() override;
/// <summary>
/// Notifies the CameraDetector to stop processing frames. Immediately stops processing.
/// </summary>
AFFDEXSDK virtual void stop() override;
/// <summary>
/// Set/reset the camera framerate. Must be positive.
/// <param name="cameraFPS">Capture framerate from the camera. Must be positive.</param>
/// <exception cref="AffdexException"> AffdexException on an invalid FPS value </exception>
/// </summary>
AFFDEXSDK void setCameraFPS(const double cameraFPS);
/// <summary>
/// Set/reset the camera id. Must be positive.
/// <param name="cameraId">Device id for the camera. </param>
/// <exception cref="AffdexException"> AffdexException on an invalid value </exception>
/// </summary>
AFFDEXSDK void setCameraId(const int cameraId);
private:
/// Masking the parent FrameDetector's process command.
using FrameDetector::process;
void onException(AffdexException);
std::shared_ptr<Camera> mCam;
};
}

并在 sdk-samples/opencv-webcam-demo 上修改 const int cameraId = 045e：02ae.cpp

#include <iostream>
#include <cstdio>
#include <string>
#include <cstdlib>
#include <memory>
#include <chrono>
#include <fstream>
#include <boost/filesystem.hpp>
#include <boost/timer/timer.hpp>
#include <boost/program_options.hpp>
#include <boost/algorithm/string.hpp>
#include "Frame.h"
#include "Face.h"
#include "FrameDetector.h"
#include "AffdexException.h"
#include "ImageListener.h"
#include "FaceListener.h"
#include "AFaceListener.hpp"
#include "PlottingImageListener.hpp"
#include "StatusListener.hpp"
using namespace std;
using namespace affdex;
/// <summary>
/// Project for demoing the Windows SDK CameraDetector class (grabbing and processing frames from the camera).
/// </summary>
//PlottingImageListener emotionlist;
int main(int argsc, char ** argsv)
{
namespace po = boost::program_options; // abbreviate namespace
std::cerr << "Hit ESCAPE key to exit app.." << endl;
shared_ptr<FrameDetector> frameDetector;
affdex::Emotions EmoXX;

try{
const std::vector<int> DEFAULT_RESOLUTION{ 640, 480 };
affdex::path DATA_FOLDER;
std::vector<int> resolution;
int process_framerate = 30;
int camera_framerate = 15;
int buffer_length = 2;
int camera_id = 045e:02ae;
unsigned int nFaces = 1;
bool draw_display = true;
int faceDetectorMode = (int)FaceDetectorMode::LARGE_FACES;
float last_timestamp = -1.0f;
float capture_fps = -1.0f;
const int precision = 2;
std::cerr.precision(precision);
std::cout.precision(precision);
po::options_description description("Project for demoing the Affdex SDK CameraDetector class (grabbing and processing frames from the camera).");
description.add_options()
("help,h", po::bool_switch()->default_value(false), "Display this help message.")
#ifdef _WIN32
("data,d", po::wvalue< affdex::path >(&DATA_FOLDER)->default_value(affdex::path(L"data"), std::string("data")), "Path to the data folder")
#else //  _WIN32
("data,d", po::value< affdex::path >(&DATA_FOLDER)->default_value(affdex::path("data"), std::string("data")), "Path to the data folder")
#endif // _WIN32
("resolution,r", po::value< std::vector<int> >(&resolution)->default_value(DEFAULT_RESOLUTION, "640 480")->multitoken(), "Resolution in pixels (2-values): width height")
("pfps", po::value< int >(&process_framerate)->default_value(30), "Processing framerate.")
("cfps", po::value< int >(&camera_framerate)->default_value(30), "Camera capture framerate.")
("bufferLen", po::value< int >(&buffer_length)->default_value(30), "process buffer size.")
("cid", po::value< int >(&camera_id)->default_value(0), "Camera ID.")
("faceMode", po::value< int >(&faceDetectorMode)->default_value((int)FaceDetectorMode::LARGE_FACES), "Face detector mode (large faces vs small faces).")
("numFaces", po::value< unsigned int >(&nFaces)->default_value(1), "Number of faces to be tracked.")
("draw", po::value< bool >(&draw_display)->default_value(true), "Draw metrics on screen.")
;
po::variables_map args;
try
{
po::store(po::command_line_parser(argsc, argsv).options(description).run(), args);
if (args["help"].as<bool>())
{
std::cout << description << std::endl;
return 0;
}
po::notify(args);
}
catch (po::error& e)
{
std::cerr << "ERROR: " << e.what() << std::endl << std::endl;
std::cerr << "For help, use the -h option." << std::endl << std::endl;
return 1;
}
if (!boost::filesystem::exists(DATA_FOLDER))
{
std::cerr << "Folder doesn't exist: " << std::string(DATA_FOLDER.begin(), DATA_FOLDER.end()) << std::endl << std::endl;;
std::cerr << "Try specifying the folder through the command line" << std::endl;
std::cerr << description << std::endl;
return 1;
}
if (resolution.size() != 2)
{
std::cerr << "Only two numbers must be specified for resolution." << std::endl;
return 1;
}
else if (resolution[0] <= 0 || resolution[1] <= 0)
{
std::cerr << "Resolutions must be positive number." << std::endl;
return 1;
}
std::ofstream csvFileStream;
std::cerr << "Initializing Affdex FrameDetector" << endl;
shared_ptr<FaceListener> faceListenPtr(new AFaceListener());
shared_ptr<PlottingImageListener> listenPtr(new PlottingImageListener(csvFileStream, draw_display));    // Instanciate the ImageListener class
shared_ptr<StatusListener> videoListenPtr(new StatusListener());
frameDetector = make_shared<FrameDetector>(buffer_length, process_framerate, nFaces, (affdex::FaceDetectorMode) faceDetectorMode);        // Init the FrameDetector Class
//Initialize detectors
frameDetector->setDetectAllEmotions(true);
frameDetector->setDetectAllExpressions(true);
frameDetector->setDetectAllEmojis(true);
frameDetector->setDetectAllAppearances(true);
frameDetector->setClassifierPath(DATA_FOLDER);
frameDetector->setImageListener(listenPtr.get());
frameDetector->setFaceListener(faceListenPtr.get());
frameDetector->setProcessStatusListener(videoListenPtr.get());
cv::VideoCapture webcam(camera_id);    //Connect to the first webcam
webcam.set(CV_CAP_PROP_FPS, camera_framerate);    //Set webcam framerate.
webcam.set(CV_CAP_PROP_FRAME_WIDTH, resolution[0]);
webcam.set(CV_CAP_PROP_FRAME_HEIGHT, resolution[1]);
std::cerr << "Setting the webcam frame rate to: " << camera_framerate << std::endl;
auto start_time = std::chrono::system_clock::now();
if (!webcam.isOpened())
{
std::cerr << "Error opening webcam!" << std::endl;
return 1;
}
std::cout << "Max num of faces set to: " << frameDetector->getMaxNumberFaces() << std::endl;
std::string mode;
switch (frameDetector->getFaceDetectorMode())
{
case FaceDetectorMode::LARGE_FACES:
mode = "LARGE_FACES";
break;
case FaceDetectorMode::SMALL_FACES:
mode = "SMALL_FACES";
break;
default:
break;
}
std::cout << "Face detector mode set to: " << mode << std::endl;
//Start the frame detector thread.
frameDetector->start();
do{
cv::Mat img;
if (!webcam.read(img))    //Capture an image from the camera
{
std::cerr << "Failed to read frame from webcam! " << std::endl;
break;
}
//Calculate the Image timestamp and the capture frame rate;
const auto milliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::system_clock::now() - start_time);
const double seconds = milliseconds.count() / 1000.f;
// Create a frame
Frame f(img.size().width, img.size().height, img.data, Frame::COLOR_FORMAT::BGR, seconds);
capture_fps = 1.0f / (seconds - last_timestamp);
last_timestamp = seconds;
frameDetector->process(f);  //Pass the frame to detector
// For each frame processed
if (listenPtr->getDataSize() > 0)
{
std::pair<Frame, std::map<FaceId, Face> > dataPoint = listenPtr->getData();
Frame frame = dataPoint.first;
std::map<FaceId, Face> faces = dataPoint.second;
// Draw metrics to the GUI
if (draw_display)
{
listenPtr->draw(faces, frame);
}
std::cerr << "timestamp: " << frame.getTimestamp()
<< " cfps: " << listenPtr->getCaptureFrameRate()
<< " pfps: " << listenPtr->getProcessingFrameRate()
<< " faces: " << faces.size() <<endl;
//<<listenPtr->emotiontype
//<< " Value = " << listenPtr->emotionlist<<endl
//<< listenPtr->*values <<endl;
//if(EmoXX.joy == 0){
//  cout << "Emotion = JOYn";
//  emo.joy = 100;
//  };
//Output metrics to the file
listenPtr->outputToFile(faces, frame.getTimestamp());
//cout << "Joy Value = " << listenPtr -> <<"n";
}

}
#ifdef _WIN32
while (!GetAsyncKeyState(VK_ESCAPE) && videoListenPtr->isRunning());
#else //  _WIN32
while (videoListenPtr->isRunning());//(cv::waitKey(20) != -1);
#endif
std::cerr << "Stopping FrameDetector Thread" << endl;
frameDetector->stop();    //Stop frame detector thread
}
catch (AffdexException ex)
{
std::cerr << "Encountered an AffdexException " << ex.what();
return 1;
}
catch (std::runtime_error err)
{
std::cerr << "Encountered a runtime error " << err.what();
return 1;
}
catch (std::exception ex)
{
std::cerr << "Encountered an exception " << ex.what();
return 1;
}
catch (...)
{
std::cerr << "Encountered an unhandled exception ";
return 1;
}
return 0;
}

，但演示程序在运行 OpenCV-网络摄像头演示时仍然无法连接 Kinect v1。 有什么方法可以使用kinect v1作为Affectiva的输入吗？