Android API教程:人脸检测(Face Detect)
2012-06-25 11:50
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构建一个人脸检测的Android Activity
你可以构建一个通用的Android Activity,我们扩展了基类ImageView,成为MyImageView,而我们需要进行检测的包含人脸的位图文件必须是565格式,API才能正常工作。被检测出来的人脸需要一个置信测度(confidence measure),这个措施定义在android.media.FaceDetector.Face.CONFIDENCE_THRESHOLD。
最重要的方法实现在setFace(),它将FaceDetector对象实例化,同时调用findFaces,结果存放在faces里,人脸的中点转移到MyImageView。代码如下:
你可以构建一个通用的Android Activity,我们扩展了基类ImageView,成为MyImageView,而我们需要进行检测的包含人脸的位图文件必须是565格式,API才能正常工作。被检测出来的人脸需要一个置信测度(confidence measure),这个措施定义在android.media.FaceDetector.Face.CONFIDENCE_THRESHOLD。
最重要的方法实现在setFace(),它将FaceDetector对象实例化,同时调用findFaces,结果存放在faces里,人脸的中点转移到MyImageView。代码如下:
public class TutorialOnFaceDetect1 extends Activity { private MyImageView mIV; private Bitmap mFaceBitmap; private int mFaceWidth = 200; private int mFaceHeight = 200; private static final int MAX_FACES = 1; private static String TAG = "TutorialOnFaceDetect"; @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); mIV = new MyImageView(this); setContentView(mIV, new LayoutParams(LayoutParams.WRAP_CONTENT, LayoutParams.WRAP_CONTENT)); // load the photo Bitmap b = BitmapFactory.decodeResource(getResources(), R.drawable.face3); mFaceBitmap = b.copy(Bitmap.Config.RGB_565, true); b.recycle(); mFaceWidth = mFaceBitmap.getWidth(); mFaceHeight = mFaceBitmap.getHeight(); mIV.setImageBitmap(mFaceBitmap); // perform face detection and set the feature points setFace(); mIV.invalidate(); } public void setFace() { FaceDetector fd; FaceDetector.Face [] faces = new FaceDetector.Face[MAX_FACES]; PointF midpoint = new PointF(); int [] fpx = null; int [] fpy = null; int count = 0; try { fd = new FaceDetector(mFaceWidth, mFaceHeight, MAX_FACES); count = fd.findFaces(mFaceBitmap, faces); } catch (Exception e) { Log.e(TAG, "setFace(): " + e.toString()); return; } // check if we detect any faces if (count > 0) { fpx = new int[count]; fpy = new int[count]; for (int i = 0; i < count; i++) { try { faces[i].getMidPoint(midpoint); fpx[i] = (int)midpoint.x; fpy[i] = (int)midpoint.y; } catch (Exception e) { Log.e(TAG, "setFace(): face " + i + ": " + e.toString()); } } } mIV.setDisplayPoints(fpx, fpy, count, 0); } }接下来的代码中,我们在MyImageView中添加setDisplayPoints() ,用来在被检测出的人脸上标记渲染。图1展示了一个标记在被检测处的人脸上处于中心位置。
// set up detected face features for display public void setDisplayPoints(int [] xx, int [] yy, int total, int style) { mDisplayStyle = style; mPX = null; mPY = null; if (xx != null && yy != null && total > 0) { mPX = new int[total]; mPY = new int[total]; for (int i = 0; i < total; i++) { mPX[i] = xx[i]; mPY[i] = yy[i]; } } } 多人脸检测 通过FaceDetector可以设定检测到人脸数目的上限。比如设置最多只检测10张脸: private static final int MAX_FACES = 10; 定位眼睛中心位置 Android人脸检测返回其他有用的信息,例同时会返回如eyesDistance,pose,以及confidence。我们可以通过eyesDistance来定位眼睛的中心位置。 下面的代码中,我们将setFace()放在doLengthyCalc()中。同时图3展示了定位眼睛中心位置的效果。 public class TutorialOnFaceDetect extends Activity { private MyImageView mIV; private Bitmap mFaceBitmap; private int mFaceWidth = 200; private int mFaceHeight = 200; private static final int MAX_FACES = 10; private static String TAG = "TutorialOnFaceDetect"; private static boolean DEBUG = false; protected static final int GUIUPDATE_SETFACE = 999; protected Handler mHandler = new Handler(){ // @Override public void handleMessage(Message msg) { mIV.invalidate(); super.handleMessage(msg); } }; @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); mIV = new MyImageView(this); setContentView(mIV, new LayoutParams(LayoutParams.WRAP_CONTENT, LayoutParams.WRAP_CONTENT)); // load the photo Bitmap b = BitmapFactory.decodeResource(getResources(), R.drawable.face3); mFaceBitmap = b.copy(Bitmap.Config.RGB_565, true); b.recycle(); mFaceWidth = mFaceBitmap.getWidth(); mFaceHeight = mFaceBitmap.getHeight(); mIV.setImageBitmap(mFaceBitmap); mIV.invalidate(); // perform face detection in setFace() in a background thread doLengthyCalc(); } public void setFace() { FaceDetector fd; FaceDetector.Face [] faces = new FaceDetector.Face[MAX_FACES]; PointF eyescenter = new PointF(); float eyesdist = 0.0f; int [] fpx = null; int [] fpy = null; int count = 0; try { fd = new FaceDetector(mFaceWidth, mFaceHeight, MAX_FACES); count = fd.findFaces(mFaceBitmap, faces); } catch (Exception e) { Log.e(TAG, "setFace(): " + e.toString()); return; } // check if we detect any faces if (count > 0) { fpx = new int[count * 2]; fpy = new int[count * 2]; for (int i = 0; i < count; i++) { try { faces[i].getMidPoint(eyescenter); eyesdist = faces[i].eyesDistance(); // set up left eye location fpx[2 * i] = (int)(eyescenter.x - eyesdist / 2); fpy[2 * i] = (int)eyescenter.y; // set up right eye location fpx[2 * i + 1] = (int)(eyescenter.x + eyesdist / 2); fpy[2 * i + 1] = (int)eyescenter.y; if (DEBUG) { Log.e(TAG, "setFace(): face " + i + ": confidence = " + faces[i].confidence() + ", eyes distance = " + faces[i].eyesDistance() + ", pose = ("+ faces[i].pose(FaceDetector.Face.EULER_X) + "," + faces[i].pose(FaceDetector.Face.EULER_Y) + "," + faces[i].pose(FaceDetector.Face.EULER_Z) + ")" + ", eyes midpoint = (" + eyescenter.x + "," + eyescenter.y +")"); } } catch (Exception e) { Log.e(TAG, "setFace(): face " + i + ": " + e.toString()); } } } mIV.setDisplayPoints(fpx, fpy, count * 2, 1); } private void doLengthyCalc() { Thread t = new Thread() { Message m = new Message(); public void run() { try { setFace(); m.what = TutorialOnFaceDetect.GUIUPDATE_SETFACE; TutorialOnFaceDetect.this.mHandler.sendMessage(m); } catch (Exception e) { Log.e(TAG, "doLengthyCalc(): " + e.toString()); } } }; t.start(); } }
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