I'm using Viola-Jones method to detect face, whenever the face is tilted there will be possibility of algorithm won't work properly.
I want to detect that movements, when it can not able to detect the face.
Can I implement this using motion detection or is there any other methods to find the movements.
Thanks in advance,
Yes you can do it by capture and compare them.
This will help you to detect them and then you can compare the x and y positions.
class DetectNose extends JPanel implements KeyListener, ActionListener {
private static final long serialVersionUID = 1L;
private static JFrame frame;
private BufferedImage image;
private CascadeClassifier face_cascade;
private Point center;
private JLabel label;
private Image scalledItemImage;
private double customY = 0;
private double customX = 0;
private Iterator<InputStream> iterator;
private ArrayList<BufferedImage> listOfCachedImages;
private int imageIndex = 1;
private int customZ = 0;
private Size size;
private Image scalledItemImageBackup;
private Point center1;
private int imgSize = 35;
private boolean isLocked;
public DetectNose(JFrame frame, List<Long> listOfOrnaments) {
super();
this.frame = frame;
this.frame.setFocusable(true);
this.frame.requestFocusInWindow();
this.frame.addKeyListener(this);
File f = null;
try {
System.out.println(System.getProperty("os.name"));
if (System.getProperty("os.name").contains("Windows")) {
f = new File("res/opencv_lib_win/opencv_java249.dll");
System.load(f.getAbsolutePath());
System.out.println("Loaded :" + f.getAbsolutePath());
} else {
f = new File("res/opencv_lib/libopencv_java246.so");
System.load(f.getAbsolutePath());
System.out.println("Loaded :" + f.getAbsolutePath());
}
} catch (Exception ex) {
ex.printStackTrace();
}
List<InputStream> ornaments = DatabaseHandler
.getOrnamentsImagesByListOfOrnaments(listOfOrnaments);
iterator = ornaments.iterator();
listOfCachedImages = new ArrayList<BufferedImage>();
try {
while (iterator.hasNext()) {
InputStream inputStream = iterator.next();
listOfCachedImages.add(ImageIO.read(inputStream));
}
setFirstOrnament();
} catch (IOException e) {
e.printStackTrace();
}
label = new JLabel(new ImageIcon(scalledItemImage));
add(label);
face_cascade = new CascadeClassifier(
"res/cascades/haarcascade_frontalface_alt_tree.xml");
if (face_cascade.empty()) {
System.out.println("--(!)Error loading A\n");
return;
} else {
System.out.println("Face classifier loaded up");
}
}
private void setFirstOrnament() {
scalledItemImage = listOfCachedImages.get(imageIndex - 1);
scalledItemImageBackup = scalledItemImage.getScaledInstance(700, 700,
BufferedImage.TYPE_INT_RGB);
scalledItemImage = scalledItemImage.getScaledInstance(imgSize, imgSize,
BufferedImage.TYPE_INT_RGB);
repaint();
System.out.println("imageIndex = " + imageIndex);
}
private void setPrevOrnament() {
if (imageIndex > 1) {
imageIndex--;
scalledItemImage = listOfCachedImages.get(imageIndex - 1);
scalledItemImageBackup = scalledItemImage.getScaledInstance(700,
700, BufferedImage.TYPE_INT_RGB);
scalledItemImage = scalledItemImage.getScaledInstance(imgSize,
imgSize, BufferedImage.TYPE_INT_RGB);
GoLiveIntermediator.nextButton.setEnabled(true);
repaint();
revalidate();
System.out.println("imageIndex = " + imageIndex);
} else {
GoLiveIntermediator.prevButton.setEnabled(false);
}
}
private void setNextOrnament() {
if (listOfCachedImages.size() > imageIndex) {
imageIndex++;
scalledItemImage = listOfCachedImages.get(imageIndex - 1);
scalledItemImageBackup = scalledItemImage.getScaledInstance(700,
700, BufferedImage.TYPE_INT_RGB);
scalledItemImage = scalledItemImage.getScaledInstance(imgSize,
imgSize, BufferedImage.TYPE_INT_RGB);
GoLiveIntermediator.prevButton.setEnabled(true);
repaint();
revalidate();
System.out.println("imageIndex = " + imageIndex);
} else {
GoLiveIntermediator.nextButton.setEnabled(false);
}
}
private BufferedImage getimage() {
return image;
}
public void setimage(BufferedImage newimage) {
image = newimage;
return;
}
public BufferedImage matToBufferedImage(Mat matrix) {
int cols = matrix.cols();
int rows = matrix.rows();
int elemSize = (int) matrix.elemSize();
byte[] data = new byte[cols * rows * elemSize];
int type;
matrix.get(0, 0, data);
switch (matrix.channels()) {
case 1:
type = BufferedImage.TYPE_BYTE_GRAY;
break;
case 3:
type = BufferedImage.TYPE_3BYTE_BGR;
// bgr to rgb
byte b;
for (int i = 0; i < data.length; i = i + 3) {
b = data[i];
data[i] = data[i + 2];
data[i + 2] = b;
}
break;
default:
return null;
}
BufferedImage image2 = new BufferedImage(cols, rows, type);
image2.getRaster().setDataElements(0, 0, cols, rows, data);
return image2;
}
public void paintComponent(Graphics g) {
try {
this.frame.requestFocusInWindow();
BufferedImage temp = getimage();
g.drawImage(temp, 0, 0, temp.getWidth(), temp.getHeight() + 50,
this);
} catch (Exception ex) {
System.out.print("Trying to load images...");
}
}
public Mat detect(Mat inputframe) {
Mat mRgba = new Mat();
Mat mGrey = new Mat();
MatOfRect faces = new MatOfRect();
inputframe.copyTo(mRgba);
inputframe.copyTo(mGrey);
Imgproc.cvtColor(mRgba, mGrey, Imgproc.COLOR_BGR2GRAY);
Imgproc.equalizeHist(mGrey, mGrey);
try {
face_cascade.detectMultiScale(mGrey, faces);
} catch (Exception e) {
System.out.print(".");
}
frame.setLocationRelativeTo(null);
frame.setResizable(false);
for (Rect rect : faces.toArray()) {
center = new Point(rect.x + rect.width * 0.5, rect.y + rect.height
* 0.5); // You can use this to point out as first detection and last detection
size = new Size(rect.width * 0.5, rect.height * 0.5);
Core.ellipse(mRgba, center, size, 0, 0, 360, new Scalar(255, 0,
255), 1, 8, 0);
repaint();
}
return mRgba;
}
Here center is the first detection point same way you can find the last detection point from the image.
