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#include <algorithm> #include <vector> #include <asserth> #include <iostreamh> template <class Type> void print_elements( Type elem ) { cout elem " "; } void (*pfi)( int ) = print_elements; int main() { int ia[] = {29,23,20,22,17,15,26,51,19,12,35,40}; vector<int,allocator> vec(ia,ia+12); sort(ia,ia+12); int *iter = upper_bound(ia,ia+12,19); assert( *iter == 20 ); sort( vecbegin(), vecend(), greater<int>() ); vector<int,allocator>::iterator iter_vec; iter_vec = upper_bound( vecbegin(), vecend(), 27, greater<int>() ); assert( *iter_vec == 26 ); // generates: 51 40 35 29 27 26 23 22 20 19 17 15 12 vecinsert( iter_vec, 27 ); for_each( vecbegin(), vecend(), pfi ); cout "\n\n"; }

Of course, the landmarks should be detected using a face and facial feature detector The face bunch graph has a stack-like structure and combines graphs of individual sample faces It is crucial that the individual graphs all have the same structure and that the nodes refer to the same ducial points All jets referring to the same ducial point (eg, all left-eye jets) are bundled together in a bunch, from which one can select any jet as an alternative description The left-eye bunch might contain a male eye, a female eye, both closed or open, and so on Each ducial point is represented by such a set of alternatives; and, from each bunch, any jet can be selected independently of the ones selected from the other bunches This provides enhanced combinatorial power that renders it so general, even if it is constituted from few graphs only.

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The standard library heap is a max-heap A max-heap is a form of binary tree represented as an array in which the key value in each node is either larger than or equal to the key value of its children (see [SEDGEWICK88] for a full discussion) (An alternative representation is a min-heap, in which the key value at any node is less than or equal to that of its children) In the standard library representation, the largest key value (think of it as the root of the tree) is always at the start of the array The following sequence of letters, for example, fulfills the requirements of a heap:

In this example, X is the root node, with the left child T and right child O Notice that the children are not required to be in sorted order (that is, the left child does not need to be less than the right) G and S are the children of T, while M and N are the children of O Similarly, A and E are the children of G, R and A are the children of S, I is the left child of M, and N is a leaf node without children The four generic heap algorithms provide support for the creation and manipulation of a heap: make_heap(), pop_heap(), push_heap(), and sort_heap() The latter three algorithms presume that the sequence marked off by the iterator pair represents an actual heap (if the sequence is not, then the run-time behavior of the algorithms is undefined) Note that a list container, because it does not support random access, cannot be used for a heap While a built-in array can be used to support a heap, the pop_heap() and push_heap() algorithms are difficult to use with arrays since the two algorithms require the resizing of the array We briefly introduce each of the four algorithms, then illustrate their use with a small program

Another variation that EBGM introduces is the use of the phase of the complex Gabor wavelet transform instead of the magnitude That is, the authors claimed that the transform phase has greater capability in nding the exact locations of the ducial points than the transform magnitude The major change in the matching algorithm is.

file:///F|/WinDDK/resources/CPPPrimer/c++primerhtm (1063 / 1065) [2001-3-29 11:32:16]

// forward declarations class EntrySlot; extern EntrySlot* look_up( string ); typedef pair< string, EntrySlot* > SymbolEntry; SymbolEntry current_entry( "author", look_up( "author" )); // if ( EntrySlot *it = look_up( "editor" )) { current_entryfirst = "editor"; current_entrysecond = it; }

the matching between a test jet and a bunch of reference jets, where the maximum similarity is proposed to be used according to Eq. (6.2).

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negotiation and key exchange for secure client-wireless AP in a way that initially is hidden from the access point. This is explained in the next subsection and is especially useful if the client initially does not trust the AP and access network provider. Note that, EAP-TTLS supports the traditional TLS mutual authentication using client certificate as well, if so desired.

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