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//
// Zinnia: Online hand recognition system with machine learning
//
// $Id: feature.cpp 17 2009-04-05 11:40:32Z taku-ku $;
//
// Copyright(C) 2008 Taku Kudo <taku@chasen.org>
//
#include <iostream>
#include <vector>
#include <cmath>
#include <algorithm>
#include "zinnia.h"
#include "feature.h"
namespace zinnia {
namespace {
static const size_t kMaxCharacterSize = 50;
struct FeatureNodeCmp {
bool operator()(const FeatureNode& x1, const FeatureNode &x2) {
return x1.index < x2.index;
}
};
float distance(const Node *n1, const Node *n2) {
const float x = n1->x - n2->x;
const float y = n1->y - n2->y;
return std::sqrt(x * x + y * y);
}
float distance2(const Node *n1) {
const float x = n1->x - 0.5;
const float y = n1->y - 0.5;
return std::sqrt(x * x + y * y);
}
float minimum_distance(const Node *first, const Node *last,
Node **best) {
if (first == last) return 0.0;
const float a = last->x - first->x;
const float b = last->y - first->y;
const float c = last->y * first->x - last->x * first->y;
float max = -1.0;
for (const Node *n = first; n != last; ++n) {
const float dist = std::fabs((a * n->y) -(b * n->x) + c);
if (dist > max) {
max = dist;
*best = const_cast<Node *>(n);
}
}
return max * max /(a * a + b * b);
}
}
bool Features::read(const Character &character) {
features_.clear();
const Node *prev = 0;
// bias term
{
FeatureNode f;
f.index = 0;
f.value = 1.0;
features_.push_back(f);
}
std::vector<std::vector<Node> > nodes(character.strokes_size());
{
const size_t height = character.height();
const size_t width = character.width();
if (height == 0 || width == 0) return false;
if (character.strokes_size() == 0) return false;
for (size_t i = 0; i < character.strokes_size(); ++i) {
const size_t ssize = character.stroke_size(i);
if (ssize == 0) {
return false;
}
nodes[i].resize(ssize);
for (size_t j = 0; j < ssize; ++j) {
nodes[i][j].x = 1.0 * character.x(i, j) / width;
nodes[i][j].y = 1.0 * character.y(i, j) / height;
}
}
}
for (size_t sid = 0; sid < nodes.size(); ++sid) {
std::vector<NodePair> node_pairs;
const Node *first = &nodes[sid][0];
const Node *last = &nodes[sid][nodes[sid].size()-1];
getVertex(first, last, 0, &node_pairs);
makeVertexFeature(sid, &node_pairs);
if (prev) {
makeMoveFeature(sid, prev, first);
}
prev = last;
}
addFeature(2000000, nodes.size());
addFeature(2000000 + nodes.size(), 10);
std::sort(features_.begin(), features_.end(), FeatureNodeCmp());
{
FeatureNode f;
f.index = -1;
f.value = 0.0;
features_.push_back(f);
}
return true;
}
void Features::addFeature(int index, float value) {
FeatureNode f;
f.index = index;
f.value = value;
features_.push_back(f);
}
void Features::makeBasicFeature(int offset,
const Node *first,
const Node *last) {
// distance
addFeature(offset + 1 , 10 * distance(first, last));
// degree
addFeature(offset + 2 ,
std::atan2(last->y - first->y, last->x - first->x));
// absolute position
addFeature(offset + 3, 10 * (first->x - 0.5));
addFeature(offset + 4, 10 * (first->y - 0.5));
addFeature(offset + 5, 10 * (last->x - 0.5));
addFeature(offset + 6, 10 * (last->y - 0.5));
// absolute degree
addFeature(offset + 7, std::atan2(first->y - 0.5, first->x - 0.5));
addFeature(offset + 8, std::atan2(last->y - 0.5, last->x - 0.5));
// absolute distance
addFeature(offset + 9, 10 * distance2(first));
addFeature(offset + 10, 10 * distance2(last));
// diff
addFeature(offset + 11, 5 * (last->x - first->x));
addFeature(offset + 12, 5 * (last->y - first->y));
}
void Features::makeMoveFeature(int sid,
const Node *first,
const Node *last) {
const int offset = 100000 + sid * 1000;
makeBasicFeature(offset, first, last);
}
void Features::makeVertexFeature(int sid,
std::vector<NodePair> *node_pairs) {
for (size_t i = 0; i < node_pairs->size(); ++i) {
if (i > kMaxCharacterSize) {
break;
}
const Node *first = (*node_pairs)[i].first;
const Node *last = (*node_pairs)[i].last;
if (!first) {
continue;
}
const int offset = sid * 1000 + 20 * i;
makeBasicFeature(offset, first, last);
}
}
void Features::getVertex(const Node *first, const Node *last,
int id,
std::vector<NodePair> *node_pairs) const {
if (node_pairs->size() <= static_cast<size_t>(id))
node_pairs->resize(id + 1);
(*node_pairs)[id].first = first;
(*node_pairs)[id].last = last;
Node *best = 0;
const float dist = minimum_distance(first, last, &best);
static const float error = 0.001;
if (dist > error) {
getVertex(first, best, id * 2 + 1, node_pairs);
getVertex(best, last, id * 2 + 2, node_pairs);
}
}
}
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