Facial Tracking... Infamous black screen

Heres what I am attemptiing to do. Take my eyes and get them to pan and track to someones face when they walk up or by.

These will be used in a halloween prop and while I think I am on the right track I wanted to reach out to the group to garner thoughts and opionins as to the process and if there is a better way by all means I am open.

Currently my plan is to use Windows 7 64bit OS: Webcam input to Processing + OpenCV talking to Arduino.

Later I will attempt to: Implement a IR Webcam Transmit via WiFi or Ethernet Expand to Audio too. Last night I spent some time installing everything and ran into a problem (which I have read about) where I get a black screen from my webcam and a haarcascade file location issue. This is where I am stuck right now.

Thanks in advance!

I have gotten the haarcascade issue fixed but now am left with the black screen issue.

Tested on processing 2 64 and 32 bit and same result. I tried the v1.5 and it had library issues so wrote that off.

Screenshot included…

Here is the code:


import processing.video.*;
import hypermedia.video.*; //import the necessary libraries
import java.awt.Rectangle;
import processing.serial.*;
import cc.arduino.*;

Capture myCapture;
OpenCV opencv;   //create the library object

// contrast/brightness values
int contrast_value    = 0;
int brightness_value  = 0;

// The arduino object:
Arduino arduino;   



void setup() {

    size( 320, 240 ); //set window size
    //windows fix addition    
    myCapture = myCapture = new Capture(this, width, height, 30);

    opencv = new OpenCV( this ); //setup openCV
    //windows fix addition
    opencv.allocate(width, height);
    //opencv.capture( width, height );   // open video stream
    //the arduino serial setup
    arduino = new Arduino(this, Arduino.list()[0], 57600);
    //list of available detection types: http://ubaa.net/shared/processing/opencv/opencv_cascade.html
    opencv.cascade( OpenCV.CASCADE_FRONTALFACE_ALT ); 
    //opencv.cascade( OpenCV.CASCADE_PROFILEFACE);
    //opencv.cascade( OpenCV.CASCADE_FULLBODY);

    // print usage
    println( "Drag mouse on X-axis inside this sketch window to change contrast" );
    println( "Drag mouse on Y-axis inside this sketch window to change brightness" );




void draw() {

    //windows fix addition
    opencv.read(); //read a new camera frame
    opencv.convert( GRAY ); //convert frame to gray scale
    opencv.contrast( contrast_value ); //apply contrast filter
    opencv.brightness( brightness_value ); //apply brightness filter

    // detect faces and put them in an array
    Rectangle[] faces = opencv.detect( 1.2, 2, OpenCV.HAAR_DO_CANNY_PRUNING, 40, 40 );

    // display gray image
    image( opencv.image(), 0, 0 );

    // draw face detection rectangles
    if(faces.length > 0)
      //the RC servo only follows the first face found. 
      int mappedValue = (int) map(faces[0].x,0,width, 0, 255); //map from screen width to 255
      arduino.analogWrite(3, mappedValue); //send data to the arduino
    for( int i=0; i<faces.length; i++ ) {
        rect( faces[i].x, faces[i].y, faces[i].width, faces[i].height );             


  change brightness and contrast values

void mouseDragged() {
    contrast_value   = (int) map( mouseX, 0, width, -128, 128 );
    brightness_value = (int) map( mouseY, 0, width, -128, 128 );



public void stop() {
    opencv.stop(); //shutdown opencv on exit

And the Arduino code is just the firmata:

#include <Servo.h>
#include <Firmata.h>

Servo servos[MAX_SERVOS];

void analogWriteCallback(byte pin, int value)
    if (IS_PIN_SERVO(pin)) {

void setup() 
    byte pin;

    Firmata.setFirmwareVersion(0, 2);
    Firmata.attach(ANALOG_MESSAGE, analogWriteCallback);

    for (pin=0; pin < TOTAL_PINS; pin++) {
        if (IS_PIN_SERVO(pin)) {

void loop() 

Any ideas?

i need the hypermedia do you have a link where i can get this ? i have some examples i found on youtube which i cant use cuz of the lack of this import

i can help with what your trying to do since im doing something similar but with 2 webcams for depth perceptions by triangulating from a compare of two images