* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details.
- *
+ * private Point readEyes( Image image, Rectangle2D rect) {
+ EyeDetector ed = new EyeDetector(image, rect);
+ return ed.detectEye();
+ }
* You should have received a copy of the GNU Lesser General Public License
* along with LEA. If not, see <http://www.gnu.org/licenses/>.
*/
* @author Florian
*/
-public class ClassifierTree {
- private Classifier classifiers[];
+public class ClassifierTree {
- public ClassifierTree(int size) {
+
+ private Classifier[] classifiers;
+
+ double x;
+
+ double y;
+
+ double width;
+
+ double height;
+
+
+ int size;
+
+
+ public ClassifierTree( int size) {
+ this.size = size;
classifiers = new Classifier[size];
+ x = -1;
+ y = -1;
+ width = -1;
+ height = -1;
}
- public void addClassifier(int idx, Classifier c) {
+ public void addClassifier( int idx, Classifier c) {
classifiers[idx] = c;
}
+
/**
* Locates a face by searching radial starting at the last known position. If lastCoordinates are
* null we simply start in the center of the image.
* @return an rectangle representing the actual face position on success or null if no face could
* be detected
*/
-
- public Rectangle2D locateFaceRadial(Image smallImage, Rectangle2D lastCoordinates) {
-
- IntegralImageData imageData = new IntegralImageData(smallImage);
- float originalImageFactor = 1;
-
- if (lastCoordinates == null) {
+
+ public void locateFaceRadial( Image smallImage) {
+
+ double px = x;
+ double py = y;
+ double pwidth = width;
+ double pheight = height;
+
+ x = -1;
+ y = -1;
+ width = -1;
+ height = -1;
+
+ IntegralImageData imageData = new IntegralImageData(smallImage);
+ float originalImageFactor = 1;
+ if (px == -1) {
+ // if(true){
// if we don't have a last coordinate we just begin in the center
- int smallImageMaxDimension = Math.min(smallImage.getWidth(), smallImage.getHeight());
- lastCoordinates =
- new Rectangle2D((smallImage.getWidth() - smallImageMaxDimension) / 2.0,
- (smallImage.getHeight() - smallImageMaxDimension) / 2.0, smallImageMaxDimension,
- smallImageMaxDimension);
- // System.out.println("lastCoordinates=" + lastCoordinates);
+ int smallImageMaxDimension = Math.min(smallImage.getWidth(), smallImage.getHeight());
+
+ px = (smallImage.getWidth() - smallImageMaxDimension) / 2.0;
+ py = (smallImage.getHeight() - smallImageMaxDimension) / 2.0;
+ pwidth = smallImageMaxDimension;
+ pheight = smallImageMaxDimension;
} else {
// first we have to scale the last coodinates back relative to the resized
// image
- lastCoordinates =
- new Rectangle2D((lastCoordinates.getX() * (1 / originalImageFactor)),
- (lastCoordinates.getY() * (1 / originalImageFactor)),
- (lastCoordinates.getWidth() * (1 / originalImageFactor)),
- (lastCoordinates.getHeight() * (1 / originalImageFactor)));
+ px = px * (1 / originalImageFactor);
+ py = py * (1 / originalImageFactor);
+ pwidth = pwidth * (1 / originalImageFactor);
+ pheight = pheight * (1 / originalImageFactor);
}
- float startFactor = (float) (lastCoordinates.getWidth() / 100.0f);
+
+ float startFactor = (float) (pwidth / 100.0f);
// first we calculate the maximum scale factor for our 200x200 image
- float maxScaleFactor = Math.min(imageData.getWidth() / 100f, imageData.getHeight() / 100f);
+ float maxScaleFactor = Math.min(imageData.getWidth() / 100f, imageData.getHeight() / 100f);
// maxScaleFactor = 1.0f;
// we simply won't recognize faces that are smaller than 40x40 px
- float minScaleFactor = 0.5f;
+ float minScaleFactor = 0.5f;
- float maxScaleDifference = Math.max(Math.abs(maxScaleFactor - startFactor), Math.abs(minScaleFactor - startFactor));
+ float maxScaleDifference = Math.max(Math.abs(maxScaleFactor - startFactor), Math.abs(minScaleFactor - startFactor));
// border for faceYes-possibility must be greater that that
- float maxBorder = 0.999f;
+ float maxBorder = 0.999f;
- int startPosX = (int) lastCoordinates.getX();
- int startPosY = (int) lastCoordinates.getX();
+ int startPosX = (int) px;
+ int startPosY = (int) py;
- int loopidx = 0;
- TERMINATE: for (float factorDiff = 0.0f; Math.abs(factorDiff) <= maxScaleDifference; factorDiff =
+ int loopidx = 0;
+ TERMINATE: for ( float factorDiff = 0.0f; Math.abs(factorDiff) <= maxScaleDifference; factorDiff =
(factorDiff + sgn(factorDiff) * 0.1f) * -1 // we alternate between
// negative and positiv
// factors
) {
if (++loopidx > 1000) {
- return null;
+ px = -1;
+ py = -1;
+ pwidth = -1;
+ pheight = -1;
+ return;
}
- float factor = startFactor + factorDiff;
+ float factor = startFactor + factorDiff;
if (factor > maxScaleFactor || factor < minScaleFactor)
continue;
// now we calculate the actualDimmension
- int actualDimmension = (int) (100 * factor);
- int maxX = imageData.getWidth() - actualDimmension;
- int maxY = imageData.getHeight() - actualDimmension;
+ int actualDimmension = (int) (100 * factor);
+ int maxX = imageData.getWidth() - actualDimmension;
+ int maxY = imageData.getHeight() - actualDimmension;
- int maxDiffX = Math.max(Math.abs(startPosX - maxX), startPosX);
- int maxDiffY = Math.max(Math.abs(startPosY - maxY), startPosY);
+ int maxDiffX = Math.max(Math.abs(startPosX - maxX), startPosX);
+ int maxDiffY = Math.max(Math.abs(startPosY - maxY), startPosY);
- int xidx = 0;
- TERMINATE: for (float xDiff = 0.1f; Math.abs(xDiff) <= maxDiffX; xDiff =
+ int xidx = 0;
+ TERMINATE: for ( float xDiff = 0.1f; Math.abs(xDiff) <= maxDiffX; xDiff =
(xDiff + sgn(xDiff) * 0.5f) * -1) {
if (++xidx > 1000) {
- return null;
+ px = -1;
+ py = -1;
+ pwidth = -1;
+ pheight = -1;
+ return;
}
- int xPos = Math.round((float) (startPosX + xDiff));
+ int xPos = Math.round((float) (startPosX + xDiff));
if (xPos < 0 || xPos > maxX)
continue;
- int yidx = 0;
+ int yidx = 0;
// yLines:
- TERMINATE: for (float yDiff = 0.1f; Math.abs(yDiff) <= maxDiffY; yDiff =
+ TERMINATE: for ( float yDiff = 0.1f; Math.abs(yDiff) <= maxDiffY; yDiff =
(yDiff + sgn(yDiff) * 0.5f) * -1) {
if (++yidx > 1000) {
- return null;
+ px = -1;
+ py = -1;
+ pwidth = -1;
+ pheight = -1;
+ return;
}
- int yPos = Math.round(startPosY + yDiff);
+ int yPos = Math.round(startPosY + yDiff);
if (yPos < 0 || yPos > maxY)
continue;
// by now we should have a valid coordinate to process which we should
// do now
- boolean backToYLines = false;
- for (int idx = 0; idx < classifiers.length; ++idx) {
- float borderline = 0.8f + (idx / (classifiers.length - 1)) * (maxBorder - 0.8f);
+ boolean backToYLines = false;
+ for ( int idx = 0; idx < size; ++idx) {
+ float borderline = 0.8f + (idx / (size - 1)) * (maxBorder - 0.8f);
if (!classifiers[idx].classifyFace(imageData, factor, xPos, yPos, borderline)) {
backToYLines = true;
break;
continue;
}
- Rectangle2D faceRect = new Rectangle2D(xPos * originalImageFactor, yPos * originalImageFactor, actualDimmension * originalImageFactor, actualDimmension * originalImageFactor);
-
- return faceRect;
+ x = xPos * originalImageFactor;
+ y = yPos * originalImageFactor;
+ width = actualDimmension * originalImageFactor;
+ height = actualDimmension * originalImageFactor;
+ return;
}
}
- // System.out.println("Time: "+(System.currentTimeMillis()-timeStart)+"ms");
- return null;
}
- private static int sgn(float value) {
+
+
+ private static int sgn( float value) {
return (value < 0 ? -1 : (value > 0 ? +1 : 1));
}
+
+ public FaceAndEyePosition getEyePosition( Image image) {
+ if (image == null) {
+ return null;
+ }
+
+ float originalImageFactor = 1;
+
+ locateFaceRadial(image);
+
+ if (width > image.getWidth() || height > image.getHeight()) {
+ return null;
+ }
+
+ EyePosition eyePosition = null;
+
+ if (x != -1) {
+ EyeDetector ed = new EyeDetector(image, x, y, width, height);
+ Point point = ed.detectEye();
+ if (point != null) {
+ eyePosition = new EyePosition(point.getX(), point.getY());
+ }
+ }
+
+ System.out.println("eyePosition=" + eyePosition);
+
+ FaceAndEyePosition fep = new FaceAndEyePosition(x, y, width, height, eyePosition);
+
+
+ return fep;
+ }
+
+
}
projects / IRC.git / blobdiff