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：
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
|
<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>
|
后台：
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
|
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,
new
BytePointer(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 =
new
CvHaarClassifierCascade(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();
}
}
|
详细的实现细节请阅读英文原文：
