大家應(yīng)該都知道幾個很常見的例子，比如在張學(xué)友的演唱會，在安檢通道檢票時，通過人像識別系統(tǒng)成功識別捉了好多在逃人員，被稱為逃犯克星；人行橫道不遵守交通規(guī)則闖紅燈的路人被人臉識別系統(tǒng)抓拍放在大屏上以示警告；參加某次活動通過人臉進(jìn)行簽到來統(tǒng)計實時人流量等等， 我現(xiàn)在也來做一個通過電視直播，追蹤畫面中所有人臉信息，并捕獲我需要的目標(biāo)人物。

具體思路及流程

基于虹軟人臉識別，對直播畫面中的每一幀圖片進(jìn)行檢測，得到圖片中所有人臉信息。可以添加目標(biāo)人物的照片，用目標(biāo)人物的人臉特征值與直播畫面幀圖片中人臉信息列表中的每一個特征值進(jìn)行比對。如果有匹配到目標(biāo)人物，把直播畫面抓拍。具體流程如下：

項目結(jié)構(gòu)

播放地址我們可以在網(wǎng)上搜索一下電視直播RTMP地址，在程序中可進(jìn)行播放

private void PlayVideo() {videoCapture = new VideoCapture(rtmp);if (videoCapture.IsOpened()){videoInfo.Filename = rtmp;videoInfo.Width = (int)videoCapture.FrameWidth;videoInfo.Height = (int)videoCapture.FrameHeight;videoInfo.Fps = (int)videoCapture.Fps;myTimer.Interval = videoInfo.Fps == 0 ? 300 : 1000 / videoInfo.Fps;IsStartPlay = true;myTimer.Start();}else{MessageBox.Show("視頻源異常");} }private void MyTimer_Elapsed(object sender, System.Timers.ElapsedEventArgs e) {try{if (IsStartPlay){lock (LockHelper){var frame = videoCapture.RetrieveMat();if (frame != null){if (frame.Width == videoInfo.Width && frame.Height == videoInfo.Height)this.SetVideoCapture(frame);elseLogHelper.Log($"bad frame");}}}}catch(Exception ex){LogHelper.Log(ex.Message);} } Bitmap btm = null; private void SetVideoCapture(Mat frame)//視頻捕獲 {try{btm = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(frame);pic_Video.Image = btm;}catch(Exception ex){LogHelper.Log(ex.Message);} }

以上這些就是在OpenCv中通過VideoCaptrue類對視頻進(jìn)行讀取操作，然后把圖像渲染到PictureBox控件上。在PictureBox的Paint事件中進(jìn)行人臉識別與比對操作。

/// <summary> /// 比對函數(shù)，將每一幀抓拍的照片和目標(biāo)人物照片進(jìn)行比對 /// </summary> /// <param name="bitmap"></param> /// <param name="e"></param> /// <returns></returns> private void CompareImgWithIDImg(Bitmap bitmap, PaintEventArgs e) {if (bitmap != null){//保證只檢測一幀，防止頁面卡頓以及出現(xiàn)其他內(nèi)存被占用情況if (isLock == false){isLock = true;Graphics g = e.Graphics;float offsetX = (pic_Video.Width * 1f / bitmap.Width);float offsetY = (pic_Video.Height * 1f / bitmap.Height);//根據(jù)Bitmap 獲取人臉信息列表List<FaceInfoModel> list = FaceUtil.GetFaceInfos(pImageEngine, bitmap);foreach (FaceInfoModel sface in list){//異步處理提取特征值和比對，不然頁面會比較卡ThreadPool.QueueUserWorkItem(new WaitCallback(delegate{try{//提取人臉特征float similarity = CompareTwoFeatures(sface.feature, imageTemp);if (similarity > threshold){this.pic_cutImg.Image = bitmap;this.Invoke((Action)(() =>{this.lbl_simiValue.Text = similarity.ToString();}));}}catch (Exception ex){Console.WriteLine(ex.Message);}}));MRECT rect = sface.faceRect;float x = rect.left * offsetX;float width = rect.right * offsetX - x;float y = rect.top * offsetY;float height = rect.bottom * offsetY - y;//根據(jù)Rect進(jìn)行畫框g.DrawRectangle(pen, x, y, width, height);trackUnit.message = "年齡：" + sface.age.ToString() + "\r\n" + "性別：" + (sface.gender == 0 ? "男" : "女");g.DrawString(trackUnit.message, font, brush, x, y + 5);}isLock = false;}} }

?單張圖片可能包含多張人臉，我們用FaceInfoModel 人臉信息實體類，把人臉信息放在此類中。

public class FaceInfoModel {/// <summary>/// 年齡/// </summary>public int age { get; set; }/// <summary>/// 性別/// </summary>public int gender { get; set; }public ASF_Face3DAngle face3dAngle { get; set; }/// <summary>/// 人臉框/// </summary>public MRECT faceRect { get; set; }/// <summary>/// 人臉角度/// </summary>public int faceOrient { get; set; }/// <summary>/// 單人臉特征/// </summary>public IntPtr feature { get; set; } }

多人臉實體類存放單人臉信息列表

public class MultiFaceModel : IDisposable {/// <summary>/// 多人臉信息/// </summary>public ASF_MultiFaceInfo MultiFaceInfo { get; private set; }/// <summary>/// 單人臉信息List/// </summary>public List<ASF_SingleFaceInfo> FaceInfoList { get; private set; }/// <summary>/// 人臉信息列表/// </summary>/// <param name="multiFaceInfo"></param>public MultiFaceModel(ASF_MultiFaceInfo multiFaceInfo) {this.MultiFaceInfo = multiFaceInfo;this.FaceInfoList = new List<ASF_SingleFaceInfo>();FaceInfoList = PtrToMultiFaceArray(multiFaceInfo.faceRects, multiFaceInfo.faceOrients, multiFaceInfo.faceNum);}/// <summary>/// 指針轉(zhuǎn)多人臉列表/// </summary>/// <param name="faceRect"></param>/// <param name="faceOrient"></param>/// <param name="length"></param>/// <returns></returns>private List<ASF_SingleFaceInfo> PtrToMultiFaceArray(IntPtr faceRect, IntPtr faceOrient, int length){List<ASF_SingleFaceInfo> FaceInfoList = new List<ASF_SingleFaceInfo>();var size = Marshal.SizeOf(typeof(int));var sizer = Marshal.SizeOf(typeof(MRECT));for (var i = 0; i < length; i++){ASF_SingleFaceInfo faceInfo = new ASF_SingleFaceInfo();MRECT rect = new MRECT();var iPtr = new IntPtr(faceRect.ToInt32() + i * sizer);rect = (MRECT)Marshal.PtrToStructure(iPtr, typeof(MRECT));faceInfo.faceRect = rect;int orient = 0;iPtr = new IntPtr(faceOrient.ToInt32() + i * size);orient = (int)Marshal.PtrToStructure(iPtr, typeof(int));faceInfo.faceOrient = orient;FaceInfoList.Add(faceInfo);}return FaceInfoList;}public void Dispose(){Marshal.FreeCoTaskMem(MultiFaceInfo.faceRects);Marshal.FreeCoTaskMem(MultiFaceInfo.faceOrients);} }

然后獲取所有人臉信息，放在列表中備用

/// <summary> /// 獲取人臉信息列表 /// </summary> /// <param name="pEngine"></param> /// <param name="bitmap"></param> /// <returns></returns> public static List<FaceInfoModel>GetFaceInfos(IntPtr pEngine,Image bitmap) {List<FaceInfoModel> listRet = new List<FaceInfoModel>();try{List<int> AgeList = new List<int>();List<int> GenderList = new List<int>();//檢測人臉，得到Rect框ASF_MultiFaceInfo multiFaceInfo = FaceUtil.DetectFace(pEngine, bitmap);MultiFaceModel multiFaceModel = new MultiFaceModel(multiFaceInfo);//人臉信息處理ImageInfo imageInfo = ImageUtil.ReadBMP(bitmap);int retCode = ASFFunctions.ASFProcess(pEngine, imageInfo.width, imageInfo.height, imageInfo.format, imageInfo.imgData, ref multiFaceInfo, FaceEngineMask.ASF_AGE| FaceEngineMask.ASF_GENDER);//獲取年齡信息ASF_AgeInfo ageInfo = new ASF_AgeInfo();retCode = ASFFunctions.ASFGetAge(pEngine, ref ageInfo);AgeList = ageInfo.PtrToAgeArray(ageInfo.ageArray, ageInfo.num);//獲取性別信息ASF_GenderInfo genderInfo = new ASF_GenderInfo();retCode = ASFFunctions.ASFGetGender(pEngine, ref genderInfo);GenderList = genderInfo.PtrToGenderArray(genderInfo.genderArray, genderInfo.num);for (int i = 0; i < multiFaceInfo.faceNum; i++){FaceInfoModel faceInfo = new FaceInfoModel();faceInfo.age = AgeList[i];faceInfo.gender = GenderList[i];faceInfo.faceRect = multiFaceModel.FaceInfoList[i].faceRect;faceInfo.feature = ExtractFeature(pEngine, bitmap, multiFaceModel.FaceInfoList[i]);//提取單人臉特征faceInfo.faceOrient = multiFaceModel.FaceInfoList[i].faceOrient;listRet.Add(faceInfo);}return listRet;//返回多人臉信息}catch {return listRet;} }

從列表中獲取到的多張人臉，在人臉上畫框作出標(biāo)識，也可以把提取的人臉信息，年齡、性別作出展示。接下來就是選擇一張目標(biāo)人物的照片，通過SDK提取目標(biāo)人物的人臉特征值作為比較對象，逐一與視頻中的人臉特征進(jìn)行比較。如果有判斷到相似度匹配的人臉，則把視頻幀圖像呈現(xiàn)出來。

/// <summary> /// 比較兩個特征值的相似度,返回相似度 /// </summary> /// <param name="feature1"></param> /// <param name="feature2"></param> /// <returns></returns> private float CompareTwoFeatures(IntPtr feature1, IntPtr feature2) {float similarity = 0.0f;//調(diào)用人臉匹配方法，進(jìn)行匹配ASFFunctions.ASFFaceFeatureCompare(pImageEngine, feature1, feature2, ref similarity);return similarity; }

之前只實現(xiàn)了從多張人臉中獲取一張最大尺寸的人臉作為比較對象，這樣視頻中也就只能對一張人臉進(jìn)行畫框標(biāo)記了，現(xiàn)在是把所有提取到的人臉均進(jìn)行標(biāo)記，并把各自特征值存在列表中，以便與目標(biāo)人臉特征值進(jìn)行匹配。

這樣也就粗略的實現(xiàn)了人臉識別追蹤，并對目標(biāo)人物進(jìn)行抓拍的功能了。

GitHub源碼已上傳:https://github.com/yumaster/FaceTracking

總結(jié)

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