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described in this paper uses Gabor wavelets as feature detectors, but evaluates the usefulness of each particular feature detector (and a corresponding (x, y) location) for distinguishing between the faces within our face database. Given the very large number of possible Gabor feature detectors and locations, we use a genetic algorithm (GA) to explore the space of possibilities, with a tness function that propagates parents with a higher ability to distinguish between the faces in the database. By selecting the Gabor feature detectors and locations that are most useful for distinguishing each person from all of the other people in the database, we de ne a unique (i.e., person-speci c) feature space for each person.

count() compares each element against value using the equality operator within the range marked off by [first,last) It returns a count of the number of elements within the container equal to value (Note that our implementation of the standard library supports an earlier specification of count()

#include <algorithm> #include <string> #include <list> #include <iterator> #include <asserth> #include <iostreamh> #include <fstreamh> /************************************************************** * text read:

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All experiments were conducted with face images from the FacePix(30) database [32]. FacePix(30) was compiled to contain face images with pose and illumination angles annotated in 1 increments. Figure 5.9 shows the apparatus that is used for capturing the face images. A video camera and a spotlight are mounted on separate annular rings, which rotate independently around a subject seated in the center. Angle markings on the rings are captured simultaneously with the face image in a video sequence, from which the required frames are extracted. This database has face images of 30 people across a spectrum of pose and illumination angles. For each person in the database, there are three sets of images. (1) The

file:///F|/WinDDK/resources/CPPPrimer/c++primerhtm (1015 / 1065) [2001-3-29 11:32:15]

Method MD5-challenge One-Time password Generic Token Card (GTC) RSA Public Key Authentication EAP-TLS RSA security Secur ID EAP EAP-Cisco Wireless (LEAP) EAP-TTLS

Alice Emma has long flowing red hair Her Daddy says when the wind blows through her hair, it looks almost alive, like a fiery bird in flight A beautiful fiery bird, he tells her, magical but untamed "Daddy, shush, there is no such thing," she tells him, at the same time wanting him to tell her more Shyly, she asks, "I mean, Daddy, is there " **************************************************************** * output of program: * count(): fiery occurs 2 times **************************************************************** */ int main() { ifstream infile( "alice_emma" ); assert ( infile != 0 ); list<string,allocator> textlines; typedef list<string,allocator>::difference_type diff_type; istream_iterator< string, diff_type > instream( infile ), eos; copy( instream, eos, back_inserter( textlines )); string search_item( "fiery" ); /************************************************************ * note: this is the Standard C++ interface for using count() * however, the current RogueWave implementation * supports the earlier version in which distance_type * had not been developed, and so count() returned its * value via a final argument to itself * * this is how the invocation should occur: * * typedef iterator_traits<InputIterator>:: * distance_type dis_type; * * dis_type elem_count; * elem_count = count( textlinesbegin(), textlinesend(), * search_item ); ************************************************************/ int elem_count = 0; list<string,allocator>::iterator ibegin = textlinesbegin(), iend = textlinesend(); // obsolete form of count() count( ibegin, iend, search_item, elem_count ); cout "count(): " < search_item " occurs " elem_count " times\n"; } count_if() template< class InputIterator, class Predicate > iterator_traits<InputIterator>::distance_type count_if( InputIterator first, InputIterator last, Predicate pred );

5

count_if() applies pred against each element within the range marked off by [first,last) It returns a count of the

file:///F|/WinDDK/resources/CPPPrimer/c++primerhtm (1016 / 1065) [2001-3-29 11:32:15]

Figure 5.9. The data capture setup for FacePix(30).

for ( vector<string>::iterator it = textbegin(); it != textend(); ++it ) cout *it ' '; cout endl;

*it;

++it;

pose angle set contains face images of each person at pose angles from +90 to 90 . (2) The no-ambient-light set contains frontal face images with a spotlight placed at angles ranging from +90 to 90 with no ambient light. (3) The ambient-light set contains frontal face images with a spot light placed at angles placed at angels from +90 to 90 in the presence of ambient light. Thus, for each person, there are three face images available for every angle, over a range of 180 . Figure 5.10 provides two examples extracted from the database, showing pose angles and illumination angles ranging from 90 to +90 in steps of 10 . For earlier work using images from this database, please refer to reference 33. Work is currently in progress to make this database publicly available.

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