I'm writing my first Qt 5 application... This uses a third-party map library (QGeoView).
I need to draw an object (something like a stylized airplane) over this map. Following the library coding guidelines, I derived from the base class QGVDrawItem my QGVAirplane.
The airplane class contains heading and position values: such values must be used to draw the airplane on the map (of course in the correct position and with correct heading). The library requires QGVDrawItem derivatives to override three base class methods:
QPainterPath projShape() const;
void projPaint(QPainter* painter);
void onProjection(QGVMap* geoMap)
The first method is used to achieve the area of the map that needs to be updated. The second is the method responsible to draw the object on the map. The third method is needed to reproject the point from the coordinate space on the map (it's not relevant for the solution of my problem).
My code looks like this:
void onProjection(QGVMap* geoMap)
{
QGVDrawItem::onProjection(geoMap);
mProjPoint = geoMap->getProjection()->geoToProj(mPoint);
}
QPainterPath projShape() const
{
QRectF _bounding = createGlyph().boundingRect();
double _size = fmax(_bounding.height(), _bounding.width());
QPainterPath _bounding_path;
_bounding_path.addRect(0,0,_size,_size);
_bounding_path.translate(mProjPoint.x(), mProjPoint.y());
return _bounding_path;
}
// This function creates the path containing the airplane glyph
// along with its label
QPainterPath createGlyph() const
{
QPainterPath _path;
QPolygon _glyph = QPolygon();
_glyph << QPoint(0,6) << QPoint(0,8) << QPoint(14,6) << QPoint(28,8) << QPoint(28,6) << QPoint(14,0);
_path.addPolygon(_glyph);
_path.setFillRule(Qt::FillRule::OddEvenFill);
_path.addText(OFF_X_TEXT, OFF_Y_TEXT, mFont , QString::number(mId));
QTransform _transform;
_transform.rotate(mHeading);
return _transform.map(_path);
}
// This function is the actual painting method
void drawGlyph(QPainter* painter)
{
painter->setRenderHints(QPainter::Antialiasing, true);
painter->setBrush(QBrush(mColor));
painter->setPen(QPen(QBrush(Qt::black), 1));
QPainterPath _path = createGlyph();
painter->translate(mProjPoint.x(), mProjPoint.y());
painter->drawPath(_path);
}
Of course:
mProjPoint is the position of the airplane,
mHeading is the heading (the direction where the airplane is pointing),
mId is a number identifying the airplane (will be displayed as a label under airplane glyph),
mColor is the color assigned to the airplane.
The problem here is the mix of rotation and translation. Transformation: since the object is rotated, projShape() methods return a bounding rectangle that's not fully overlapping the object drawn on the map...
I also suspect that the center of the object is not correctly pointed on mProjPoint. I tried many times trying to translate the bounding rectangle to center the object without luck.
Another minor issue is the fillup of the font... the label under the airplane glyph is not solid, but it is filled with the same color of the airplane.
How can I fix this?
Generically speaking, the general pattern for rotation is to scale about the origin first and then finish with your final translation.
The following is pseudocode, but it illustrates the need to shift your object's origin to (0, 0) prior to doing any rotation or scaling. After the rotate and scale are done, the object can be moved back from (0, 0) back to where it came from. From here, any post-translation step may be applied.
translate( -origin.x, -origin.y );
rotate( angle );
scale( scale.x, scale y);
translate( origin.x, origin.y );
translate( translation.x, translation.y )
I finally managed to achieve the result I meant....
QPainterPath projShape() const
{
QPainterPath _path;
QRectF _glyph_bounds = _path.boundingRect();
QPainterPath _textpath;
_textpath.addText(0, 0, mFont, QString::number(mId));
QRectF _text_bounds = _textpath.boundingRect();
_textpath.translate(_glyph_bounds.width()/2-_text_bounds.width()/2, _glyph_bounds.height()+_text_bounds.height());
_path.addPath(_textpath);
QTransform _transform;
_transform.translate(mProjPoint.x(),mProjPoint.y());
_transform.rotate(360-mHeading);
_transform.translate(-_path.boundingRect().width()/2, -_path.boundingRect().height()/2);
return _transform.map(_path);
}
void projPaint(QPainter* painter)
{
painter->setRenderHint(QPainter::Antialiasing, true);
painter->setRenderHint(QPainter::TextAntialiasing, true);
painter->setRenderHint(QPainter::SmoothPixmapTransform, true);
painter->setRenderHint(QPainter::HighQualityAntialiasing, true);
painter->setBrush(QBrush(mColor));
painter->setPen(QPen(QBrush(Qt::black), 1));
painter->setFont(mFont);
QPainterPath _path = projShape();
painter->drawPath(_path);
}
Unluckly I still suffer the minor issue with text fill mode:
I would like to have a solid black fill for the text instead of the mColor fill I use for the glyph/polygon.
Where should I start? I can see plenty of face recognition and analysis using Python, Java script but how about Processing ?
I want to determine the distance by using 2 points between upper and lower lip at their highest and lowest point via webcam to use it in further project.
any help would be appreciated
If you want to do it in Processing alone you can use Greg Borenstein's OpenCV for Processing library:
You can start with the Face Detection example
Once you detect a face, you can detect a mouth within the face rectangle using OpenCV.CASCADE_MOUTH.
Once you have mouth detected maybe you can get away with using the mouth bounding box height. For more detail you use OpenCV to threshold that rectangle. Hopefully the open mouth will segment nicely from the rest of the skin. Finding contours should give you lists of points you can work with.
For something a lot more exact, you can use Jason Saragih's CLM FaceTracker, which is available as an OpenFrameworks addon. OpenFrameworks has similarities to Processing. If you do need this sort of accuracy in Processing you can run FaceOSC in the background and read the mouth coordinates in Processing using oscP5
Update
For the first option, using HAAR cascade classifiers, turns out there are a couple of issues:
The OpenCV Processing library can load one cascade and a second instance will override the first.
The OpenCV.CASCADE_MOUTH seems to work better for closed mouths, but not very well with open mouths
To get past the 1st issue, you can use the OpenCV Java API directly, bypassing OpenCV Processing for multiple cascade detection.
There are couple of parameters that can help the detection, such as having idea of the bounding box of the mouth before hand to pass as a hint to the classifier.
I've done a basic test using a webcam on my laptop and measure the bounding box for face and mouth at various distances. Here's an example:
import gab.opencv.*;
import org.opencv.core.*;
import org.opencv.objdetect.*;
import processing.video.*;
Capture video;
OpenCV opencv;
CascadeClassifier faceDetector,mouthDetector;
MatOfRect faceDetections,mouthDetections;
//cascade detections parameters - explanations from Mastering OpenCV with Practical Computer Vision Projects
int flags = Objdetect.CASCADE_FIND_BIGGEST_OBJECT;
// Smallest object size.
Size minFeatureSizeFace = new Size(50,60);
Size maxFeatureSizeFace = new Size(125,150);
Size minFeatureSizeMouth = new Size(30,10);
Size maxFeatureSizeMouth = new Size(120,60);
// How detailed should the search be. Must be larger than 1.0.
float searchScaleFactor = 1.1f;
// How much the detections should be filtered out. This should depend on how bad false detections are to your system.
// minNeighbors=2 means lots of good+bad detections, and minNeighbors=6 means only good detections are given but some are missed.
int minNeighbors = 4;
//laptop webcam face rectangle
//far, small scale, ~50,60px
//typing distance, ~83,91px
//really close, ~125,150
//laptop webcam mouth rectangle
//far, small scale, ~30,10
//typing distance, ~50,25px
//really close, ~120,60
int mouthHeightHistory = 30;
int[] mouthHeights = new int[mouthHeightHistory];
void setup() {
opencv = new OpenCV(this,320,240);
size(opencv.width, opencv.height);
noFill();
frameRate(30);
video = new Capture(this,width,height);
video.start();
faceDetector = new CascadeClassifier(dataPath("haarcascade_frontalface_alt2.xml"));
mouthDetector = new CascadeClassifier(dataPath("haarcascade_mcs_mouth.xml"));
}
void draw() {
//feed cam image to OpenCV, it turns it to grayscale
opencv.loadImage(video);
opencv.equalizeHistogram();
image(opencv.getOutput(), 0, 0 );
//detect face using raw Java OpenCV API
Mat equalizedImg = opencv.getGray();
faceDetections = new MatOfRect();
faceDetector.detectMultiScale(equalizedImg, faceDetections, searchScaleFactor, minNeighbors, flags, minFeatureSizeFace, maxFeatureSizeFace);
Rect[] faceDetectionResults = faceDetections.toArray();
int faces = faceDetectionResults.length;
text("detected faces: "+faces,5,15);
if(faces >= 1){
Rect face = faceDetectionResults[0];
stroke(0,192,0);
rect(face.x,face.y,face.width,face.height);
//detect mouth - only within face rectangle, not the whole frame
Rect faceLower = face.clone();
faceLower.height = (int) (face.height * 0.65);
faceLower.y = face.y + faceLower.height;
Mat faceROI = equalizedImg.submat(faceLower);
//debug view of ROI
PImage faceImg = createImage(faceLower.width,faceLower.height,RGB);
opencv.toPImage(faceROI,faceImg);
image(faceImg,width-faceImg.width,0);
mouthDetections = new MatOfRect();
mouthDetector.detectMultiScale(faceROI, mouthDetections, searchScaleFactor, minNeighbors, flags, minFeatureSizeMouth, maxFeatureSizeMouth);
Rect[] mouthDetectionResults = mouthDetections.toArray();
int mouths = mouthDetectionResults.length;
text("detected mouths: "+mouths,5,25);
if(mouths >= 1){
Rect mouth = mouthDetectionResults[0];
stroke(192,0,0);
rect(faceLower.x + mouth.x,faceLower.y + mouth.y,mouth.width,mouth.height);
text("mouth height:"+mouth.height+"~px",5,35);
updateAndPlotMouthHistory(mouth.height);
}
}
}
void updateAndPlotMouthHistory(int newHeight){
//shift older values by 1
for(int i = mouthHeightHistory-1; i > 0; i--){
mouthHeights[i] = mouthHeights[i-1];
}
//add new value at the front
mouthHeights[0] = newHeight;
//plot
float graphWidth = 100.0;
float elementWidth = graphWidth / mouthHeightHistory;
for(int i = 0; i < mouthHeightHistory; i++){
rect(elementWidth * i,45,elementWidth,mouthHeights[i]);
}
}
void captureEvent(Capture c) {
c.read();
}
One very imortant note to make: I've copied cascade xml files from the OpenCV Processing library folder (~/Documents/Processing/libraries/opencv_processing/library/cascade-files) to the sketch's data folder. My sketch is OpenCVMouthOpen, so the folder structure looks like this:
OpenCVMouthOpen
├── OpenCVMouthOpen.pde
└── data
├── haarcascade_frontalface_alt.xml
├── haarcascade_frontalface_alt2.xml
├── haarcascade_frontalface_alt_tree.xml
├── haarcascade_frontalface_default.xml
├── haarcascade_mcs_mouth.xml
└── lbpcascade_frontalface.xml
If you don't copy the cascades files and use the code as it is you won't get any errors, but the detection simply won't work. If you want to check, you can do
println(faceDetector.empty())
at the end of the setup() function and if you get false, the cascade has been loaded and if you get true, the cascade hasn't been loaded.
You may need to play with the minFeatureSize and maxFeatureSize values for face and mouth for your setup. The second issue, cascade not detecting wide open mouth very well is tricky. There might be an already trained cascade for open mouths, but you'd need to find it. Otherwise, with this method you may need to train one yourself and that can be a bit tedious.
Nevertheless, notice that there is an upside down plot drawn on the left when a mouth is detected. In my tests I noticed that the height isn't super accurate, but there are noticeable changes in the graph. You may not be able to get a steady mouth height, but by comparing current to averaged previous height values you should see some peaks (values going from positive to negative or vice-versa) which give you an idea of a mouth open/close change.
Although searching through the whole image for a mouth as opposed to a face only can be a bit slower and less accurate, it's a simpler setup. It you can get away with less accuracy and more false positives on your project this could be simpler:
import gab.opencv.*;
import java.awt.Rectangle;
import org.opencv.objdetect.Objdetect;
import processing.video.*;
Capture video;
OpenCV opencv;
Rectangle[] faces,mouths;
//cascade detections parameters - explanations from Mastering OpenCV with Practical Computer Vision Projects
int flags = Objdetect.CASCADE_FIND_BIGGEST_OBJECT;
// Smallest object size.
int minFeatureSize = 20;
int maxFeatureSize = 150;
// How detailed should the search be. Must be larger than 1.0.
float searchScaleFactor = 1.1f;
// How much the detections should be filtered out. This should depend on how bad false detections are to your system.
// minNeighbors=2 means lots of good+bad detections, and minNeighbors=6 means only good detections are given but some are missed.
int minNeighbors = 6;
void setup() {
size(320, 240);
noFill();
stroke(0, 192, 0);
strokeWeight(3);
video = new Capture(this,width,height);
video.start();
opencv = new OpenCV(this,320,240);
opencv.loadCascade(OpenCV.CASCADE_MOUTH);
}
void draw() {
//feed cam image to OpenCV, it turns it to grayscale
opencv.loadImage(video);
opencv.equalizeHistogram();
image(opencv.getOutput(), 0, 0 );
Rectangle[] mouths = opencv.detect(searchScaleFactor,minNeighbors,flags,minFeatureSize, maxFeatureSize);
for (int i = 0; i < mouths.length; i++) {
text(mouths[i].x + "," + mouths[i].y + "," + mouths[i].width + "," + mouths[i].height,mouths[i].x, mouths[i].y);
rect(mouths[i].x, mouths[i].y, mouths[i].width, mouths[i].height);
}
}
void captureEvent(Capture c) {
c.read();
}
I was mentioning segmenting/thresholding as well. Here's a rough example using the lower part of a detected face just a basic threshold, then some basic morphological filters (erode/dilate) to cleanup the thresholded image a bit:
import gab.opencv.*;
import org.opencv.core.*;
import org.opencv.objdetect.*;
import org.opencv.imgproc.Imgproc;
import java.awt.Rectangle;
import java.util.*;
import processing.video.*;
Capture video;
OpenCV opencv;
CascadeClassifier faceDetector,mouthDetector;
MatOfRect faceDetections,mouthDetections;
//cascade detections parameters - explanations from Mastering OpenCV with Practical Computer Vision Projects
int flags = Objdetect.CASCADE_FIND_BIGGEST_OBJECT;
// Smallest object size.
Size minFeatureSizeFace = new Size(50,60);
Size maxFeatureSizeFace = new Size(125,150);
// How detailed should the search be. Must be larger than 1.0.
float searchScaleFactor = 1.1f;
// How much the detections should be filtered out. This should depend on how bad false detections are to your system.
// minNeighbors=2 means lots of good+bad detections, and minNeighbors=6 means only good detections are given but some are missed.
int minNeighbors = 4;
//laptop webcam face rectangle
//far, small scale, ~50,60px
//typing distance, ~83,91px
//really close, ~125,150
float threshold = 160;
int erodeAmt = 1;
int dilateAmt = 5;
void setup() {
opencv = new OpenCV(this,320,240);
size(opencv.width, opencv.height);
noFill();
video = new Capture(this,width,height);
video.start();
faceDetector = new CascadeClassifier(dataPath("haarcascade_frontalface_alt2.xml"));
mouthDetector = new CascadeClassifier(dataPath("haarcascade_mcs_mouth.xml"));
}
void draw() {
//feed cam image to OpenCV, it turns it to grayscale
opencv.loadImage(video);
opencv.equalizeHistogram();
image(opencv.getOutput(), 0, 0 );
//detect face using raw Java OpenCV API
Mat equalizedImg = opencv.getGray();
faceDetections = new MatOfRect();
faceDetector.detectMultiScale(equalizedImg, faceDetections, searchScaleFactor, minNeighbors, flags, minFeatureSizeFace, maxFeatureSizeFace);
Rect[] faceDetectionResults = faceDetections.toArray();
int faces = faceDetectionResults.length;
text("detected faces: "+faces,5,15);
if(faces > 0){
Rect face = faceDetectionResults[0];
stroke(0,192,0);
rect(face.x,face.y,face.width,face.height);
//detect mouth - only within face rectangle, not the whole frame
Rect faceLower = face.clone();
faceLower.height = (int) (face.height * 0.55);
faceLower.y = face.y + faceLower.height;
//submat grabs a portion of the image (submatrix) = our region of interest (ROI)
Mat faceROI = equalizedImg.submat(faceLower);
Mat faceROIThresh = faceROI.clone();
//threshold
Imgproc.threshold(faceROI, faceROIThresh, threshold, width, Imgproc.THRESH_BINARY_INV);
Imgproc.erode(faceROIThresh, faceROIThresh, new Mat(), new Point(-1,-1), erodeAmt);
Imgproc.dilate(faceROIThresh, faceROIThresh, new Mat(), new Point(-1,-1), dilateAmt);
//find contours
Mat faceContours = faceROIThresh.clone();
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(faceContours, contours, new Mat(), Imgproc.RETR_EXTERNAL , Imgproc.CHAIN_APPROX_SIMPLE);
//draw contours
for(int i = 0 ; i < contours.size(); i++){
MatOfPoint contour = contours.get(i);
Point[] points = contour.toArray();
stroke(map(i,0,contours.size()-1,32,255),0,0);
beginShape();
for(Point p : points){
vertex((float)p.x,(float)p.y);
}
endShape();
}
//debug view of ROI
PImage faceImg = createImage(faceLower.width,faceLower.height,RGB);
opencv.toPImage(faceROIThresh,faceImg);
image(faceImg,width-faceImg.width,0);
}
text("Drag mouseX to control threshold: " + threshold+
"\nHold 'e' and drag mouseX to control erodeAmt: " + erodeAmt+
"\nHold 'd' and drag mouseX to control dilateAmt: " + dilateAmt,5,210);
}
void mouseDragged(){
if(keyPressed){
if(key == 'e') erodeAmt = (int)map(mouseX,0,width,1,6);
if(key == 'd') dilateAmt = (int)map(mouseX,0,width,1,10);
}else{
threshold = mouseX;
}
}
void captureEvent(Capture c) {
c.read();
}
This could be improved a bit by using YCrCb colour space to segment skin better, but overall you notice that there are quite a few variables to get right which doesn't make this a very flexible setup.
You will be much better results using FaceOSC and reading the values you need in Processing via oscP5. Here is a slightly simplified version of the FaceOSCReceiver Processing example focusing mainly on mouth:
import oscP5.*;
OscP5 oscP5;
// num faces found
int found;
// pose
float poseScale;
PVector posePosition = new PVector();
// gesture
float mouthHeight;
float mouthWidth;
void setup() {
size(640, 480);
frameRate(30);
oscP5 = new OscP5(this, 8338);
oscP5.plug(this, "found", "/found");
oscP5.plug(this, "poseScale", "/pose/scale");
oscP5.plug(this, "posePosition", "/pose/position");
oscP5.plug(this, "mouthWidthReceived", "/gesture/mouth/width");
oscP5.plug(this, "mouthHeightReceived", "/gesture/mouth/height");
}
void draw() {
background(255);
stroke(0);
if(found > 0) {
translate(posePosition.x, posePosition.y);
scale(poseScale);
noFill();
ellipse(0, 20, mouthWidth* 3, mouthHeight * 3);
}
}
// OSC CALLBACK FUNCTIONS
public void found(int i) {
println("found: " + i);
found = i;
}
public void poseScale(float s) {
println("scale: " + s);
poseScale = s;
}
public void posePosition(float x, float y) {
println("pose position\tX: " + x + " Y: " + y );
posePosition.set(x, y, 0);
}
public void mouthWidthReceived(float w) {
println("mouth Width: " + w);
mouthWidth = w;
}
public void mouthHeightReceived(float h) {
println("mouth height: " + h);
mouthHeight = h;
}
// all other OSC messages end up here
void oscEvent(OscMessage m) {
if(m.isPlugged() == false) {
println("UNPLUGGED: " + m);
}
}
On OSX you can simply download the compiled FaceOSC app.
On other operating systems you may need to setup OpenFrameworks, download ofxFaceTracker and compile FaceOSC yourself.
It's really hard to answer general "how do I do this" type questions. Stack Overflow is designed for specific "I tried X, expected Y, but got Z instead" type questions. But I'll try to answer in a general sense:
You need to break your problem down into smaller pieces.
Step 1: Can you get a webcam feed showing in your sketch? Don't worry about the computer vision stuff for a second. Just get the camera connected. Do some research and try something out.
Step 2: Can you detect facial features in that video? You might try doing it yourself, or you might use one of the many libraries listed in the Videos and Vision section of the Processing libraries page.
Step 3: Read the documentation on those libraries. Try them out. You might have to make a bunch of little example sketches using each library until you find one you like. We can't do this for you, as which one is right for you depends on you. If you're confused about something specific we can try to help you, but we can't really help you with picking out a library.
Step 4: Once you've done a bunch of example programs and picked out a library, start working towards your goal. Can you detect facial features using the library? Get just that part working. Once you have that working, can you detect changes like opening or closing a mouth?
Work on one small step at a time. If you get stuck, post an MCVE along with a specific technical question, and we'll go from there. Good luck.
I'm using WebCamTexture to get input from the camera (iOS&Android). However, since this is raw input, the rotation is wrong when rendered to a texture. I read around a lot, and found this (look at the bottom): WebCamTexture rotated and flipped on iPhone
His code (but with test-values):
Quaternion rotation = Quaternion.Euler(45f, 30f, 90f);
Matrix4x4 rotationMatrix = Matrix4x4.TRS(Vector3.zero, rotation, new Vector3(1, 1, 1));
material.SetMatrix("_Rotation", rotationMatrix);
But whatever value I use, nothing happens (neither in the editor or on devices)...
Thanks!
Edit
After some intense testing, I found that material.SetMatrix, SetFloat, SetWhatever has NO effect (not setting the value) unless it's declared inside the "Properties"-block. Looking at unity:s own example, this should't have to (and can't) be done for a matrix (can't be declared inside Properties, only inside the CGProgram). So... How do you set a matrix then? Or what else am I doing wrong?
You should be using: WebCamTexture.videoRotationAngle
its designed to solve exactly this problem, read more about this here.
Example code:
using UnityEngine;
using System.Collections;
public class ExampleClass : MonoBehaviour {
public WebCamTexture webcamTexture;
public Quaternion baseRotation;
void Start() {
webcamTexture = new WebCamTexture();
renderer.material.mainTexture = webcamTexture;
baseRotation = transform.rotation;
webcamTexture.Play();
}
void Update() {
transform.rotation = baseRotation * Quaternion.AngleAxis(webcamTexture.videoRotationAngle, Vector3.up);
}
}
Just rotate the camera to 90 degrees along the z axis (the camera is which is rendering the webcamtexture gameobject).
This is my first post. I hope the answer to this is not so obviously found- I could not find it.
I have a collision detection project in as3- I know that odd shapes will not hit the built-in detection methods perfectly, but supposedly perfect rectangles are exactly the shape of the bounding boxes they are contained it- yet- running the code below, I find that every once in a while a shape will not seem to trigger the test at the right time, and I cannot figure out why.
I have below two classes- one creates a rectangle shape, and a main class which creates a shape with random width and height, animates them from the top of the screen at a random x value towards the bottom at a set rate, mimicking gravity. If a shape hits the bottom of the screen, it situates itself half way between the displayed and undisplayed portions of the stage about its lower boundary, as expected- but when two shapes eventually collide, the expected behavior does not always happen- the expected behavior being that the shape that has fallen and collided with another shape should stop and rest on the top of the shape it has made contact with, whereas sometimes the falling shape will fall partially or completely through the shape it should have collided with.
does anyone have any idea why this is?
here are my two classes below in their entirety:
// box class //
package
{
import flash.display.Sprite;
public class Box extends Sprite
{
private var w:Number;
private var h:Number;
private var color:uint;
public var vx:Number = 0;
public var vy:Number = 0;
public function Box(width:Number=50,
height:Number=50,
color:uint=0xff0000)
{
w = width;
h = height;
this.color = color;
init();
}
public function init():void{
graphics.beginFill(color);
graphics.drawRect(0, 0, w, h);
graphics.endFill();
}
}
}
//main class//
package
{
import flash.display.Sprite;
import flash.events.Event;
public class Boxes extends Sprite
{
private var box:Box;
private var boxes:Array;
private var gravity:Number = 16;
public function Boxes()
{
init();
}
private function init():void
{
boxes = new Array();
createBox();
addEventListener(Event.ENTER_FRAME, onEnterFrame);
}
private function onEnterFrame(event:Event):void
{
box.vy += gravity;
box.y += box.vy;
if(box.y + box.height / 2 > stage.stageHeight)
{
box.y = stage.stageHeight - box.height / 2;
createBox();
}
for(var i:uint = 0; i < boxes.length; i++)
{
if(box != boxes[i] && box.hitTestObject(boxes[i]))
{
box.y = boxes[i].y - box.height;
createBox();
}
}
}
private function createBox():void
{
box = new Box(Math.random() * 40 + 10,
Math.random() * 40 + 10,
0xffaabb)
box.x = Math.random() *stage.stageWidth;
addChild(box);
boxes.push(box);
}
}
}
Make sure box.vy never exceeds any of the heights of any boxes created. Otherwise, it is possible the box can pass through other boxes while falling. (if box.vy = 40 and boxes[i].height=30, it is possible to pass right over it).
Just add a check:
if(box.vy>terminalVelocity)box.vy=terminalVelocity)
Where terminalVelocity is whatever the minimum height a box can be (in your code, it looks like 10). If you really want those small boxes, you will have to use something more precise than hitTestObject.