Android 如何使用FaceDetector进行人脸跟踪？

我希望像这样使用FaceDetector进行人脸跟踪。

在此示例中，将ByteBuffer设置为Frame.imageData，如下所示

 outputFrame = new Frame.Builder()
            .setImageData(mPendingFrameData, mPreviewSize.getWidth(),
                                mPreviewSize.getHeight(), ImageFormat.NV21)
            .setId(mPendingFrameId)
            .setTimestampMillis(mPendingTimeMillis)
            .setRotation(mRotation)
            .build();

//data is image data as byte.
bitmap = BitmapFactory.decodeByteArray(data, 0, data.length);
outputFrame = new Frame.Builder()
            .setBitmap(bitmap)
            .setId(frameId)
            .setTimestampMillis(time)
            .build();

    FaceDetector fd = new FaceDetector.Builder(this.context)
                        .setTrackingEnabled(true)
                        .setClassificationType(FaceDetector.ALL_CLASSIFICATIONS)
                        .build();

        fd.setProcessor(new MultiProcessor.Builder<Face>(new GraphicFaceTrackerFactory()).build());
        fd.receiveFrame(frame);

     private class GraphicFaceTrackerFactory implements MultiProcessor.Factory<Face> {
        @Override
        public Tracker<Face> create(Face face) {
            return new GraphicFaceTracker();
        }
     }

private class GraphicFaceTracker extends Tracker<Face> {

    GraphicFaceTracker() {}

    @Override
    public void onNewItem(int faceId, Face face) {
        Log.d(Constants.LOG_TAG, "onNewItem. Face Id => "+faceId);//here
    }

    @Override
    public void onUpdate(FaceDetector.Detections<Face> detectionResults, Face face) {
    }

    @Override
    public void onMissing(FaceDetector.Detections<Face> detectionResults) {

    }

    @Override
    public void onDone() {

    }
}

但是，我将位图设置为这样的帧

 outputFrame = new Frame.Builder()
            .setImageData(mPendingFrameData, mPreviewSize.getWidth(),
                                mPreviewSize.getHeight(), ImageFormat.NV21)
            .setId(mPendingFrameId)
            .setTimestampMillis(mPendingTimeMillis)
            .setRotation(mRotation)
            .build();

//data is image data as byte.
bitmap = BitmapFactory.decodeByteArray(data, 0, data.length);
outputFrame = new Frame.Builder()
            .setBitmap(bitmap)
            .setId(frameId)
            .setTimestampMillis(time)
            .build();

    FaceDetector fd = new FaceDetector.Builder(this.context)
                        .setTrackingEnabled(true)
                        .setClassificationType(FaceDetector.ALL_CLASSIFICATIONS)
                        .build();

        fd.setProcessor(new MultiProcessor.Builder<Face>(new GraphicFaceTrackerFactory()).build());
        fd.receiveFrame(frame);

     private class GraphicFaceTrackerFactory implements MultiProcessor.Factory<Face> {
        @Override
        public Tracker<Face> create(Face face) {
            return new GraphicFaceTracker();
        }
     }

private class GraphicFaceTracker extends Tracker<Face> {

    GraphicFaceTracker() {}

    @Override
    public void onNewItem(int faceId, Face face) {
        Log.d(Constants.LOG_TAG, "onNewItem. Face Id => "+faceId);//here
    }

    @Override
    public void onUpdate(FaceDetector.Detections<Face> detectionResults, Face face) {
    }

    @Override
    public void onMissing(FaceDetector.Detections<Face> detectionResults) {

    }

    @Override
    public void onDone() {

    }
}

像这样使用面部检测器

 outputFrame = new Frame.Builder()
            .setImageData(mPendingFrameData, mPreviewSize.getWidth(),
                                mPreviewSize.getHeight(), ImageFormat.NV21)
            .setId(mPendingFrameId)
            .setTimestampMillis(mPendingTimeMillis)
            .setRotation(mRotation)
            .build();

//data is image data as byte.
bitmap = BitmapFactory.decodeByteArray(data, 0, data.length);
outputFrame = new Frame.Builder()
            .setBitmap(bitmap)
            .setId(frameId)
            .setTimestampMillis(time)
            .build();

    FaceDetector fd = new FaceDetector.Builder(this.context)
                        .setTrackingEnabled(true)
                        .setClassificationType(FaceDetector.ALL_CLASSIFICATIONS)
                        .build();

        fd.setProcessor(new MultiProcessor.Builder<Face>(new GraphicFaceTrackerFactory()).build());
        fd.receiveFrame(frame);

     private class GraphicFaceTrackerFactory implements MultiProcessor.Factory<Face> {
        @Override
        public Tracker<Face> create(Face face) {
            return new GraphicFaceTracker();
        }
     }

private class GraphicFaceTracker extends Tracker<Face> {

    GraphicFaceTracker() {}

    @Override
    public void onNewItem(int faceId, Face face) {
        Log.d(Constants.LOG_TAG, "onNewItem. Face Id => "+faceId);//here
    }

    @Override
    public void onUpdate(FaceDetector.Detections<Face> detectionResults, Face face) {
    }

    @Override
    public void onMissing(FaceDetector.Detections<Face> detectionResults) {

    }

    @Override
    public void onDone() {

    }
}

FaceDetector fd=newfacedetector.Builder（this.context）
.SetTrackinEnabled（真）
.setClassificationType（FaceDetector.ALL_分类）
.build（）；
setProcessor（新的多处理器.Builder（新的GraphicFaceTrackerFactory（））.build（））；
fd.接收帧（帧）；
私有类GraphicFaceTrackerFactory实现多处理器工厂{
@凌驾
公共跟踪器创建（面）{
返回新的GraphicFaceTracker（）；
}
}
私有类GraphicFaceTracker扩展跟踪程序{
GraphicFaceTracker（）{}
@凌驾
公共void onNewItem（int-faceId，Face）{
Log.d（Constants.Log_标记，“onNewItem.Face Id=>”+faceId）；//这里
}
@凌驾
公共空隙更新（面检测器。检测检测结果，面）{
}
@凌驾
缺失时的公共空白（FaceDetector.Detections detectionResults）{
}
@凌驾
公用电话{
}
}

我希望在onNewItem（）中输入相同的faceId，只要相同的面仍在帧中，但每次输入的id都不同

你有什么想法吗

【附加信息】
・在我的应用程序中，它以7.5fps的速度连续拍摄静态照片