基于 HTML5 的人脸识别技术

演示了通过 HTML5 + JavaScript 技术实现的人脸识别，目前仅适用于 Chrome浏览器，首先需要在地址栏输入 about:flags ，然后找到“启用 MediaStream” 这一项，点击“启用” 后重启 Chrome 浏览器

然后打开下面地址：

http://neave.com/webcam/html5/face/

当你摇头晃脑的时候，那副眼镜会跟着移动并帮你戴上眼镜。

你可以查看网页源码来了解具体的实现细节。

———————————–我是分界线———————————————

这是一篇国外的文章，介绍如何通过 WebRTC、OpenCV 和 WebSocket 技术实现在 Web 浏览器上的人脸识别，架构在 Jetty 之上。

实现的效果包括：

还能识别眼睛

人脸识别的核心代码：

页面：

XML/HTML Code复制内容到剪贴板

<div>
<video id="live" width="320" height="240" autoplay style="display: inline;">video>
<canvas width="320" id="canvas" height="240" style="display: inline;">canvas>
div>

<script type="text/javascript">
var video = $("#live").get()[0];
var canvas = $("#canvas");
var ctx = canvas.get()[0].getContext('2d');

navigator.webkitGetUserMedia("video",
function(stream) {
video.src = webkitURL.createObjectURL(stream);
},
function(err) {
console.log("Unable to get video stream!")
}
)

timer = setInterval(
function () {
ctx.drawImage(video, 0, 0, 320, 240);
}, 250);
script>

 

JavaScript Code复制内容到剪贴板

public class FaceDetection {

private static final String CASCADE_FILE ="resources/haarcascade_frontalface_alt.xml";

private int minsize = 20;
private int group = 0;
private double scale = 1.1;

/**
* Based on FaceDetection example from JavaCV.
*/
public byte[] convert(byte[] imageData) throws IOException {
// create image from supplied bytearray
IplImage originalImage = cvDecodeImage(cvMat(1, imageData.length,CV_8UC1, newBytePointer(imageData)));

// Convert to grayscale for recognition
IplImage grayImage = IplImage.create(originalImage.width(), originalImage.height(), IPL_DEPTH_8U, 1);
cvCvtColor(originalImage, grayImage, CV_BGR2GRAY);

// storage is needed to store information during detection
CvMemStorage storage = CvMemStorage.create();

// Configuration to use in analysis
CvHaarClassifierCascade cascade = newCvHaarClassifierCascade(cvLoad(CASCADE_FILE));

// We detect the faces.
CvSeq faces = cvHaarDetectObjects(grayImage, cascade, storage, scale, group, minsize);

// We iterate over the discovered faces and draw yellow rectangles around them.
for (int i = 0; i < faces.total(); i++) {
CvRect r = new CvRect(cvGetSeqElem(faces, i));
cvRectangle(originalImage, cvPoint(r.x(), r.y()),
cvPoint(r.x() + r.width(), r.y() + r.height()),
CvScalar.YELLOW, 1, CV_AA, 0);
}

// convert the resulting image back to an array
ByteArrayOutputStream bout = new ByteArrayOutputStream();
BufferedImage imgb = originalImage.getBufferedImage();
ImageIO.write(imgb, "png", bout);
return bout.toByteArray();
}
}