文件列表:

data (0, 2000-02-17)
data\eye.net (31058, 1999-05-04)
data\eye.wet (23548, 1999-05-04)
data\eyemask25x15.pgm (517, 1999-05-04)
data\face-fr-1a.net (56006, 1999-05-04)
data\face-fr-1a.wet (63877, 1999-05-04)
data\face-fr-1b.net (56006, 1999-05-04)
data\face-fr-1b.wet (63975, 1999-05-04)
data\face-fr-2a.net (56006, 1999-05-04)
data\face-fr-2a.wet (63978, 1999-05-04)
data\face-fr-2b.net (56006, 1999-05-04)
data\face-fr-2b.wet (63891, 1999-05-04)
data\face-hr-1a.net (56006, 1999-05-04)
data\face-hr-1a.wet (63929, 1999-05-04)
data\face-hr-1b.net (56006, 1999-05-04)
data\face-hr-1b.wet (64020, 1999-05-04)
data\face-hr-2a.net (56006, 1999-05-04)
data\face-hr-2a.wet (63883, 1999-05-04)
data\face-hr-2b.net (56006, 1999-05-04)
data\face-hr-2b.wet (63937, 1999-05-04)
data\face-pr-1a.net (56006, 1999-05-04)
data\face-pr-1a.wet (64047, 1999-05-04)
data\face-pr-1b.net (56006, 1999-05-04)
data\face-pr-1b.wet (63898, 1999-05-04)
data\face-pr-2a.net (56006, 1999-05-04)
data\face-pr-2a.wet (63925, 1999-05-04)
data\face-pr-2b.net (56006, 1999-05-04)
data\face-pr-2b.wet (63894, 1999-05-04)
data\face-with-rot-1.net (36009, 1999-05-04)
data\face-with-rot-1.wet (39250, 1999-05-04)
data\face-with-rot-2.net (36009, 1999-05-04)
data\face-with-rot-2.wet (39213, 1999-05-04)
data\face12.net (36009, 1999-05-04)
data\face12.param (224, 1999-05-04)
data\face12.wet (27570, 1999-05-04)
data\face13.net (51833, 1999-05-04)
data\face13.param (224, 1999-05-04)
data\face13.wet (41448, 1999-05-04)
data\face14.net (36009, 1999-05-04)
data\face14.wet (27615, 1999-05-04)
... ...

CMU Face Detector ----------------- By Henry A. Rowley (har@cs.cmu.edu, http://www.cs.cmu.edu/~har/ ) Developed at Carnegie Mellon University for the face detection project. Library and code may be used for non-commercial research, evaluations, or demonstrations, but please provide appropriate acknowledgements, and let har@cs.cmu.edu how you are using it. Thanks! The upright face detector contained here is derived from the one presented in "http://www.cs.cmu.edu/~har/faces.html#upright". The rotation invariant detector (run by "rot_test") is described in "http://www.cs.cmu.edu/~har/faces.html#rotated". Overview -------- The interfaces provided by this library were developed for a number of different projects (which may make the names of the interface functions seem a little odd). The most complete interface is the Track_FindAllFaces() interface, which not only gives you face locations but also eye locations. If you received a binary distribution, you can skip directly to the section "Using the Detector Library". Build Instructions for Library (Unix) ------------------------------------- 1) Create a directory for the architecture you are building for, under the directory containing this README file. Directories for the SGI, the Alpha running OSF/1 3.1, and SunOS should already exist. 2) cd into that directory. 3) Type "gmake -f ../Makefile". (Normal make probably won't work) Currently the Makefiles are only set up to recognize SGIs, Alphas, and SunOS machines, and this package should build cleanly on either of these systems. If the machine type is not recognized, it uses the same parameters as SunOS; this can be changed by modifying the Makefiles. Build Instructions for the Library (Windows) -------------------------------------------- This package has been compiled using Windows NT, but it should also work with Windows 95. To build the package, cd to the "bcc" or "msvc" directories, and run "make -f ..\Makefile.bcc" (for Borland's C++) or "nmake -f ..\Makefile.msvc" (for Microsoft's Visual C++). The library and executables will be placed in the current directory. Using the Detector Library -------------------------- The architecture directory will contain a library (libdetect.a) which can be linked with your code to do face detection. There are several example programs in the "example" subdirectory. They make use of "detect.h" file in the "include" directory. The comments in that header file have more information about the interfaces to the detector. The interface to the detector is fairly straightforward--you give it an array of unsigned chars, which represent pixel intensities. It returns an array of structures, which contain the coordinates of rectangles surrounding all the faces it finds. A separate interface allows you to restrict the search area to a rectangular region, which can significantly improve the performance. Test Cases ---------- You should see several executables in the directory appropriate to your architecture. These executables each test one of the interfaces to the face detector. For example, "xavier_test" can be run as follows: xavier_test ../test/henry.pgm It should give the following output: Loading image... Finding all faces in image... 2 faces found: (224,109)-(274,159) (172,179)-(221,229) Finding first face in image in a vertical stripe... Found a face at (174,182)-(224,231) The "im_test", "im2_test", "imorient_test", and "xaviercolor_test" programs use the ../test/henry.ppm and ../test/profile.ppm test images, while "slow_test", "imgray_test", "xavier_test", "siemens_test", "rot_test", and "track_test" use the ../test/henry.pgm, ../test/henry2.pgm, ../test/profile.pgm, ../test/albert.pgm, ../test/albert-rot35.pgm, and ../test/henry-gray.pgm images, and "siemens2_test" and "astro_test" use the ../test/henry.gif image. The only interface that returns eye locations is Track_FindAllFaces(), in the test program "track_test". Xavier_FindOneFace and Xavier_FindOneFaceColor have extra optimizations including using motion and color to speed up the search, and stopping the search as soon as one face is found. im_test, im2_test, imorient_test, xaviercolor_test all take color images in .ppm format as input, the names of which are passed on the command line. slow_test, imgray_test, xavier_test, siemens_test, and track_test all take grayscale .pgm images via standard input. Finally, siemens2_test and astro_test take images in .gif format, and convert to grayscale for processing. Each program is used to test a separate interface to the face detector. The features of the individual interfaces are described below: im_test: converts color image to grayscale, locates all faces. also tests the functions for updating the color model over time, based on faces that are detected. useful if you are processing video sequences. im2_test: converts color image to grayscale, finds faces, allows you to adjust various thresholds imorient_test: attempts to detect faces from different views, from profile to frontal. Converts color image to grayscale for processing xaviercolor_test: uses color information to narrow search region. Two interfaces, one locates all faces, the other locates the largest face, and has many optimization parameters imgray_test: same as im_test, but takes a grayscale image xavier_test: same as xaviercolor_test, but takes a grayscale image siemens_test: like imgray_test, but allows you to specify a mask for which portions of the image to examine. Also locates eyes track_test: like imgray_test, but also locates eyes siemens2_test: like siemens_test, but reads .gif images slow_test: slow version of detector, which test out different networks and arbitration modes. Reads .pgm (grayscale) files. astro_test: does nothing (never detects faces, runs very slowly) rot_test: in-plane rotation invariant detector. Reads .pgm files. rot_test_ext: in-plane rotation invariant detector. Reads .pgm, writes .pgm files with the extracted face windows. More information about how to use each interface is given in facedetector/include/detect.h. The programs rely on several data files in the "data" subdirectory; the call to SetDataPath() sets up the directory in which to look for these files (which should always be located at ../data related to the executable). These files are as follows: *.net, *.param, and *.wet: Neural network architectures and weight files *.pgm: Mask files defining the input regions for the neural networks mlist: Contains a list of .ppm files, used to build the skin color model *.ppm: Files containing skin color samples (any dark regions are not included in the model). Questions? ---------- If you have any difficulty with the detector, I'll be happy to help. Send me e-mail at har@cs.cmu.edu.

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