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Implementation of a flexible face-recognition pipeline,
including pluggable detectors, aligners, feature extractors
and recognisers.
/**
* Copyright (c) 2011, The University of Southampton and the individual contributors.
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* * Neither the name of the University of Southampton nor the names of its
* contributors may be used to endorse or promote products derived from this
* software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
* ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
package org.openimaj.image.processing.face.feature;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import org.openimaj.feature.FeatureVectorProvider;
import org.openimaj.feature.FloatFV;
import org.openimaj.image.FImage;
import org.openimaj.image.pixel.Pixel;
import org.openimaj.image.processing.face.alignment.AffineAligner;
import org.openimaj.image.processing.face.detection.keypoints.FKEFaceDetector;
import org.openimaj.image.processing.face.detection.keypoints.FacialKeypoint;
import org.openimaj.image.processing.face.detection.keypoints.FacialKeypoint.FacialKeypointType;
import org.openimaj.image.processing.face.detection.keypoints.KEDetectedFace;
import org.openimaj.io.ReadWriteableBinary;
import org.openimaj.io.wrappers.ReadableListBinary;
import org.openimaj.io.wrappers.WriteableListBinary;
import org.openimaj.math.geometry.point.Point2d;
import org.openimaj.math.geometry.point.Point2dImpl;
import Jama.Matrix;
/**
* A {@link FacialFeature} that is built by concatenating each of the normalised
* facial part patches from a detected face.
*
* @author Jonathon Hare ([email protected])
*
*/
public class FacePatchFeature implements FacialFeature, FeatureVectorProvider {
/**
* A {@link FacialFeatureExtractor} for producing {@link FacialFeature}s
*
* @author Jonathon Hare ([email protected])
*
*/
public static class Extractor implements FacialFeatureExtractor {
/**
* Default constructor
*/
public Extractor() {
}
@Override
public FacePatchFeature extractFeature(KEDetectedFace face) {
final FacePatchFeature f = new FacePatchFeature();
f.initialise(face);
return f;
}
@Override
public void readBinary(DataInput in) throws IOException {
// Do nothing
}
@Override
public byte[] binaryHeader() {
// Do nothing
return null;
}
@Override
public void writeBinary(DataOutput out) throws IOException {
// Do nothing
}
}
/**
* A {@link FacialKeypoint} with an associated feature
*
* @author Jonathon Hare ([email protected])
*/
public static class DetectedFacePart extends FacialKeypoint implements ReadWriteableBinary {
float[] featureVector;
int featureRadius;
/**
* Default constructor
*/
public DetectedFacePart() {
super();
}
/**
* Construct with the given parameters
*
* @param type
* the type of keypoint
* @param position
* the position of the keypoint
*/
public DetectedFacePart(FacialKeypointType type, Point2d position) {
super(type, position);
}
/**
* @return the image patch around the keypoint
*/
public FImage getImage() {
final FImage image = new FImage(2 * featureRadius + 1, 2 * featureRadius + 1);
for (int i = 0, rr = -featureRadius; rr <= featureRadius; rr++) {
for (int cc = -featureRadius; cc <= featureRadius; cc++) {
final float r2 = rr * rr + cc * cc;
if (r2 <= featureRadius * featureRadius) { // inside circle
final float value = featureVector[i++];
image.pixels[rr + featureRadius][cc + featureRadius] = value < -3 ? 0
: value >= 3 ? 1 : (3f + value) / 6f;
}
}
}
return image;
}
@Override
public void readBinary(DataInput in) throws IOException {
super.readBinary(in);
final int sz = in.readInt();
if (sz < 0) {
featureVector = null;
} else {
featureVector = new float[sz];
for (int i = 0; i < sz; i++)
featureVector[i] = in.readFloat();
}
featureRadius = in.readInt();
}
@Override
public byte[] binaryHeader() {
return this.getClass().getName().getBytes();
}
@Override
public void writeBinary(DataOutput out) throws IOException {
super.writeBinary(out);
if (featureVector == null) {
out.writeInt(-1);
} else {
out.writeInt(featureVector.length);
for (final float f : featureVector)
out.writeFloat(f);
}
out.writeInt(featureRadius);
}
}
final static int[][] VP = {
{ 0 }, // EYE_LEFT_LEFT,
{ 1 }, // EYE_LEFT_RIGHT,
{ 2 }, // EYE_RIGHT_LEFT,
{ 3 }, // EYE_RIGHT_RIGHT,
{ 4 }, // NOSE_LEFT,
{ 5 }, // NOSE_MIDDLE,
{ 6 }, // NOSE_RIGHT,
{ 7 }, // MOUTH_LEFT,
{ 8 }, // MOUTH_RIGHT,
{ 0, 1 }, // EYE_LEFT_CENTER,
{ 2, 3 }, // EYE_RIGHT_CENTER,
{ 1, 2 }, // NOSE_BRIDGE,
{ 7, 8 } }; // MOUTH_CENTER
protected FloatFV featureVector;
/** The radius of the descriptor samples about each point */
protected int radius = 10;
/** The scale of the descriptor samples about each point */
protected float scl = 1;
protected List faceParts = new ArrayList();
/**
* Default constructor.
*/
public FacePatchFeature() {
}
protected void initialise(KEDetectedFace face) {
extractFeatures(face);
this.featureVector = createFeatureVector();
}
protected FloatFV createFeatureVector() {
final int length = faceParts.get(0).featureVector.length;
final FloatFV fv = new FloatFV(faceParts.size() * length);
for (int i = 0; i < faceParts.size(); i++) {
System.arraycopy(faceParts.get(i).featureVector, 0, fv.values, i * length, length);
}
return fv;
}
protected void extractFeatures(KEDetectedFace face) {
final Matrix T0 = AffineAligner.estimateAffineTransform(face);
final Matrix T = T0.copy();
final FImage J = FKEFaceDetector.pyramidResize(face.getFacePatch(), T);
final FacialKeypoint[] pts = face.getKeypoints();
faceParts.clear();
final float pyrScale = (float) (T0.get(0, 2) / T.get(0, 2));
// build a list of the center of each patch wrt image J
final Point2dImpl[] P0 = new Point2dImpl[VP.length];
for (int j = 0; j < P0.length; j++) {
final int[] vp = VP[j];
final int vp0 = vp[0];
P0[j] = new Point2dImpl(0, 0);
if (vp.length == 1) {
P0[j].x = pts[vp0].position.x / pyrScale;
P0[j].y = pts[vp0].position.y / pyrScale;
} else {
final int vp1 = vp[1];
P0[j].x = ((pts[vp0].position.x + pts[vp1].position.x) / 2.0f) / pyrScale;
P0[j].y = ((pts[vp0].position.y + pts[vp1].position.y) / 2.0f) / pyrScale;
}
}
// Prebuild transform
final List transformed = new ArrayList();
final List nontransformed = new ArrayList();
for (int rr = -radius; rr <= radius; rr++) {
for (int cc = -radius; cc <= radius; cc++) {
final float r2 = rr * rr + cc * cc;
if (r2 <= radius * radius) { // inside circle
// Note: do transform without the translation!!!
final float px = (float) (cc * scl * T.get(0, 0) + rr * scl * T.get(0, 1));
final float py = (float) (cc * scl * T.get(1, 0) + rr * scl * T.get(1, 1));
transformed.add(new Point2dImpl(px, py));
nontransformed.add(new Pixel(cc, rr));
}
}
}
for (int j = 0; j < VP.length; j++) {
final DetectedFacePart pd = new DetectedFacePart(FacialKeypointType.valueOf(j),
new Point2dImpl(P0[j].x * pyrScale, P0[j].y * pyrScale));
faceParts.add(pd);
pd.featureVector = new float[transformed.size()];
int n = 0;
float mean = 0;
float m2 = 0;
for (int i = 0; i < transformed.size(); i++) {
final Point2dImpl XYt = transformed.get(i);
final double xt = XYt.x + P0[j].x;
final double yt = XYt.y + P0[j].y;
final float val = J.getPixelInterp(xt, yt);
pd.featureVector[i] = val;
n++;
final float delta = val - mean;
mean = mean + delta / n;
m2 = m2 + delta * (val - mean);
}
float std = (float) Math.sqrt(m2 / (n - 1));
if (std <= 0)
std = 1;
for (int i = 0; i < transformed.size(); i++) {
pd.featureVector[i] = (pd.featureVector[i] - mean) / std;
}
}
}
@Override
public FloatFV getFeatureVector() {
return this.featureVector;
}
@Override
public void readBinary(DataInput in) throws IOException {
featureVector = new FloatFV();
featureVector.readBinary(in);
radius = in.readInt();
scl = in.readFloat();
new ReadableListBinary(faceParts) {
@Override
protected DetectedFacePart readValue(DataInput in) throws IOException {
final DetectedFacePart v = new DetectedFacePart();
v.readBinary(in);
return v;
}
}.readBinary(in);
}
@Override
public byte[] binaryHeader() {
return this.getClass().getName().getBytes();
}
@Override
public void writeBinary(DataOutput out) throws IOException {
featureVector.writeBinary(out);
out.writeInt(radius);
out.writeFloat(scl);
new WriteableListBinary(faceParts) {
@Override
protected void writeValue(DetectedFacePart v, DataOutput out) throws IOException {
v.writeBinary(out);
}
}.writeBinary(out);
}
}