文件列表:

fd\augmentlr.m (328, 2001-03-22)
fd\augmentud.m (331, 2001-03-22)
fd\buildimvector.m (414, 2001-03-14)
fd\buildmask.m (1478, 2001-03-14)
fd\buildresvector.m (265, 2001-03-14)
fd\classifynn.m (388, 2001-03-21)
fd\createnn.m (359, 2001-03-14)
fd\facescan.m (2361, 2001-03-23)
fd\facetrain.m (3657, 2001-03-23)
fd\loadimages.m (521, 2001-03-14)
fd\normalize.m (1244, 2001-03-14)
fd\params.m (257, 2001-03-23)
fd\rowley_henry_1998_1.pdf (1411194, 2009-01-11)
fd\scaled\AmyBW.JPG (9659, 2001-03-22)
fd\scaled\GradBW.JPG (10841, 2001-03-22)
fd\scaled\HeadsBW.JPG (10424, 2001-03-23)
fd\scaled\n01-x.PNG (718, 2001-03-14)
fd\scaled\n02-x.PNG (710, 2001-03-14)
fd\scaled\n03-x.PNG (708, 2001-03-14)
fd\scaled\n04-x.PNG (750, 2001-03-14)
fd\scaled\n05-x.PNG (713, 2001-03-14)
fd\scaled\n06-x.PNG (730, 2001-03-14)
fd\scaled\n07-x.PNG (708, 2001-03-14)
fd\scaled\n08-x.PNG (707, 2001-03-14)
fd\scaled\n09-x.PNG (718, 2001-03-14)
fd\scaled\n10-x.PNG (731, 2001-03-14)
fd\scaled\n11-x.PNG (739, 2001-03-14)
fd\scaled\n12-x.PNG (738, 2001-03-14)
fd\scaled\n13-x.PNG (690, 2001-03-14)
fd\scaled\n14-x.PNG (732, 2001-03-14)
fd\scaled\n15-x.PNG (743, 2001-03-14)
fd\scaled\n16-x.PNG (720, 2001-03-14)
fd\scaled\n17-x.PNG (726, 2001-03-14)
fd\scaled\n18-x.PNG (725, 2001-03-14)
fd\scaled\n19-x.PNG (748, 2001-03-14)
fd\scaled\n20-x.PNG (715, 2001-03-14)
fd\scaled\n21-x.PNG (717, 2001-03-14)
fd\scaled\n22-x.PNG (719, 2001-03-14)
... ...

Student: Scott Sanner Email: ssanner@cs.stanford.edu Course: CS223B, Winter Final Project: Rowley-Beluja-Kanade Face Detector System Requirements =================== Matlab 5.x with the Image Processing and Neural Net toolboxes. Unpacking the files =================== Create a directory for the project and untar the tarfile using the command 'tar -xvf fd.tar'. This should create a number of m-files in the current directory and a subdirectory of images used to train the neural net. Running the Face Detector ========================= To build a trained, face-detection neural net, simply run the 'facetrain' script. The two global variables needed from this script are 'NET' which is the trained neural net, and 'MASK' which is the mask used to define the area inside a rectangle which will be tested for facehood. To run the face-detector on an image using the 'facescan' function, simply pass 'NET', 'MASK', a double array of the grayscale image, and a few parameters governing the detection threshold and image scanning characteristics. Check the 'facescan.m' file for more information on good values for the paramters. File Listing ============ M-Files (Main Files) -------------------- facetrain.m - The main neural net training script which loads all required training files, builds the needed data structures, and trains and tests the neural net facescan.m - The main image face-scanning function. Simply pass this function the neural net, image, mask, and a few parameters governing the detection threshold and scanning characteristics. See the contents of this file for for good default values for the parameters. M-Files (Neural Net Utilities) ------------------------------ createnn.m - Creates a neural net given the input, hidden, and output unit characteristics. simnn.m - Simple formats the data for presentation to the neural net. trainnn.m - Trains a neural net given labeled data and a percentage to use for the validation set (which it constructs). classifynn.m - Normalizes an image and returns the classification value from the neural net. M-Files (Image Utilities) ------------------------- buildimvector.m - Builds an image vector from a rectangular image array. Used to convert data so that it can be used by the neural net for training. buildresvector.m - Builds a result vector to match the image vector. buildmask.m - Builds a rectangulary binary mask array for face images. normalize.m - Normalizes an image by subtracting a linear lighting plane and rescaling the grayscale distribution histogram. augmentlr.m - Augments an image set with the left-right flipped versions of the images. augmentud.m - Augments an image set with the upside- down versions of the images. M-Files (Image Loading/Display) ------------------------------- loadimages.m - Loads a set of images according to the given pattern set. showimages.m - Subplots a set of images in an image array. Image Data (Using wildcards '#') -------------------------------- scaled/n##-x.PNG - Non-face files used for training scaled/s##-n.PNG - Face data of normal pose for s## scaled/s##-c.PNG - Face data of center lighting pose for s## scaled/s##-l.PNG - Face data of left lighting pose for s## scaled/s##-r.PNG - Face data of right lighting pose for s## scaled/s##-g.PNG - Face data of pose with glasses for s##

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