一种快速的无监督的向量化方法做地标识别

这是我之前写的一篇文章extremely fast codebook learning for landmark recognition。主要是利用Random projection trees and low dimensional manifolds这篇文章进行地标识别，论文的主要思想简单：利用random projection tree 随机选择一个方向进行投影，将投影之后的data根据阈值进行左右子树的划分，这里的思想有点类似于lsh在欧几里得空间的做法了，只不过这里的bin只有左右两个，分裂到一定深度停止（比如10），利用多颗树构成森林，消除随机性带来的不确定性，提高算法的泛化性。算法的速度非常快。在实际使用中也比其他的无监督式的做法要快的多。这里主要贴上个人写的主要c++实现代码，具体代码将放在https://github.com/guoyilin/ERPF：

struct TreeNode {        vector<int> indices;        int index;        int height;        float thresholds[2];        vector<float> w;        TreeNode* left;        TreeNode* right;};class SpatialTree {private:        vector<vector<float> > *data;        void splitF(TreeNode *node);        void splitFbyFixed(TreeNode *node);        vector<float>        dot(const vector<vector<float> > &v1, const vector<float> &v2);        float dot(const vector<float> &v1, const vector<float> &v2);        float find_percentile(float percentage, const vector<float> &w);        void save_rpTree(const string& rptree_file);        void save_rpTree_sub(TreeNode *tree, ptree &pt);public:        float spill;        string rule;        TreeNode *root;        int leaf_count;        int min_items;        int samples_rp;        int height;        int dimension;        SpatialTree();        vector<float> stringTovector(string& w);        void print_rpTree(TreeNode *tree);        SpatialTree(vector<vector<float> > &data, const string &rule, float spill,                        int height);        void create_rpTree(const string& rptree_file);        void load_rpTree(const string& rptree_file);        vector<int> retrievalLeaf(vector<float> &feature);};#endif

<pre name="code" class="cpp">void SpatialTree::save_rpTree_sub(TreeNode *tree, ptree &pt) {        if (tree->index > -1)//// leaf                pt.put("xmlattr.index", tree->index);        else {                ////not leaf                string w_string;                for (std::vector<float>::const_iterator iter = tree->w.begin(); iter                                != tree->w.end(); ++iter)                        if (w_string.empty()) {                                ostringstream ostr;                                ostr << *iter;                                w_string += ostr.str();                                w_string += ",";                        } else {                                ostringstream ostr;                                ostr << *iter;                                w_string += ostr.str();                                w_string += ",";                        }                w_string = w_string.substr(0, w_string.size() - 1);                pt.put("xmlattr.w", w_string);                pt.put("xmlattr.t0", tree->thresholds[0]);                pt.put("xmlattr.t1", tree->thresholds[1]);                ptree left_child;                ptree right_child;                left_child.put("xmlattr.height", tree->left->height);                save_rpTree_sub(tree->left, left_child);                pt.put_child("left", left_child);                right_child.put("xmlattr.height", tree->right->height);                save_rpTree_sub(tree->right, right_child);                pt.put_child("right", right_child);        }}void SpatialTree::save_rpTree(const string& rptree_file) {        ptree pt;        ptree root_tree;        root_tree.put("xmlattr.height", root->height);        root_tree.put("xmlattr.count", this->leaf_count);        root_tree.put("xmlattr.dimension", this->dimension);        root_tree.put("xmlattr.min_items", this->min_items);        root_tree.put("xmlattr.samples_rp", this->samples_rp);        root_tree.put("xmlattr.rule", this->rule);        root_tree.put("xmlattr.spill", this->spill);        if (root->height != 0) {                save_rpTree_sub(root, root_tree);        }        pt.put_child("root", root_tree);        boost::property_tree::write_xml(rptree_file.c_str(), pt);}SpatialTree::SpatialTree() {        this->leaf_count = 0;        this->min_items = 64;        this->samples_rp = 10;}float SpatialTree::find_percentile(float percentage, const vector<float> &w) {        vector<float> wx_sort(w);        std::sort(wx_sort.begin(), wx_sort.end());        int n = wx_sort.size();        float i = (n + 1) * percentage;        int j = (int) floor(i);        float g = fmod(i, 1);        if (g == 0)                return wx_sort[j];        else                return (1 - g) * wx_sort[j - 1] + g * wx_sort[j];}vector<int> SpatialTree::retrievalLeaf(vector<float> &feature) {        vector<int> leafs;        queue<TreeNode *> queue;        queue.push(root);        while (!queue.empty()) {                TreeNode *item = queue.front();                if (item->index != -1)                        leafs.push_back(item->index);                else {                        float wx = this->dot(item->w, feature);                        if (wx >= item->thresholds[0])                                queue.push(item->right);                        if (wx < item->thresholds[1])                                queue.push(item->left);                }                queue.pop();        }        return leafs;}void SpatialTree::print_rpTree(TreeNode *tree) {        if (tree->index != -1) {                cout << "leaf:" << tree->height << endl;                return;        }        for (int i = 0; i < tree->w.size(); i++) {                cout << tree->w[i] << " ";        }        if (tree->index == -1) {                cout << "height:" << tree->height << "\t";                cout << "w size:" << tree->w.size() << endl;                print_rpTree(tree->left);                print_rpTree(tree->right);        }}vector<float> SpatialTree::stringTovector(string& w) {        vector<float> result;        vector<string> strs;        boost::split(strs, w, boost::is_any_of(","));        for (int i = 0; i < strs.size(); i++) {                float value = atof(strs[i].c_str());                result.push_back(value);        }        return result;}void SpatialTree::load_rpTree(const string& rptree_file) {        ptree pt;        read_xml(rptree_file, pt);        this->root = new TreeNode();        root->height = pt.get<int> ("root.xmlattr.height");        this->min_items = pt.get<int> ("root.xmlattr.min_items");        this->samples_rp = pt.get<int> ("root.xmlattr.samples_rp");        this->dimension = pt.get<int> ("root.xmlattr.dimension");        this->leaf_count = pt.get<int> ("root.xmlattr.count");        queue<ptree> q;        queue<TreeNode *> q2;        ptree root_pt;        root_pt = pt.get_child("root");        q.push(root_pt);        q2.push(root);        while (!q.empty()) {                ptree node = q.front();                TreeNode *current = q2.front();                int index = node.get<int> ("xmlattr.index", -1);                if (index != -1) {                        current->index = node.get<int> ("xmlattr.index", -1);                } else {                        current->index = -1;                        current->thresholds[0] = node.get<float> ("xmlattr.t0");                        current->thresholds[1] = node.get<float> ("xmlattr.t1");                        string w = node.get<string> ("xmlattr.w");                        current->w = stringTovector(w);                        TreeNode *leftNode = new TreeNode();                        current->left = leftNode;                        TreeNode *rightNode = new TreeNode();                        current->right = rightNode;                        leftNode->height = node.get<int> ("left.xmlattr.height");                        rightNode->height = node.get<int> ("right.xmlattr.height");                        ptree left = node.get_child("left");                        ptree right = node.get_child("right");                        q.push(left);                        q.push(right);                        q2.push(current->left);                        q2.push(current->right);                }                q.pop();                q2.pop();        }}vector<float> SpatialTree::dot(const vector<vector<float> > &v1,                const vector<float> &v2) {        if (v2.size() == 0)                cout << "error in compute dot!" << endl;        vector<float> result(v1.size());        for (int j = 0; j < v1.size(); j++)                for (int i = 0; i < v2.size(); i++) {                        result[j] += v1[j][i] * v2[i];                }        return result;}float SpatialTree::dot(const vector<float> &v1, const vector<float> &v2) {        if (v1.size() != v2.size() || v1.size() == 0) {                cout << "error in compute dot!" << endl;        }        float result = 0;        for (int i = 0; i < v1.size(); i++) {                result += v1[i] * v2[i];        }        return result;}void SpatialTree::splitF(TreeNode *node) {        std::random_device rd;        std::mt19937 gen(rd());        std::normal_distribution<float> distribution(0, 1);        vector<vector<float> > W(this->samples_rp);        for (int i = 0; i < W.size(); i++) {                vector<float> v(this->dimension);                W[i] = v;        }        vector<float> sum(this->samples_rp);        for (int i = 0; i < this->samples_rp; i++) {                for (int j = 0; j < this->dimension; j++) {                        W[i][j] = (float) distribution(gen);                        sum[i] += W[i][j];                }        }        for (int i = 0; i < this->samples_rp; i++) {                for (int j = 0; j < this->dimension; j++) {                        W[i][j] = W[i][j] / sum[i];                }        }        vector<float> min_val(this->samples_rp, INFINITY);        vector<float> max_val(this->samples_rp, -INFINITY);        for (int i = 0; i < node->indices.size(); i++) {                vector<float> point = (*this->data)[i];                vector<float> Wx = this->dot(W, point);                for (int j = 0; j < min_val.size(); j++) {                        if (min_val[j] > Wx[j])                                min_val[j] = Wx[j];                }                for (int j = 0; j < max_val.size(); j++) {                        if (max_val[j] < Wx[j])                                max_val[j] = Wx[j];                }        }        int max_index = -1;        float max_value = -INFINITY;        for (int i = 0; i < max_val.size(); i++) {                max_val[i] = max_val[i] - min_val[i];                if (max_value < max_val[i]) {                        max_value = max_val[i];                        max_index = i;                }        }        node->w = W[max_index];}SpatialTree::SpatialTree(vector<vector<float> > &data, const string &rule,                float spill, int height) {        this->data = &data;        this->rule = rule;        this->spill = spill;        min_items = 64;        samples_rp = 10;        this->height = height;        this->leaf_count = 0;}void SpatialTree::create_rpTree(const string& rptree_file) {        vector<int> indices(data->size());        for (vector<int>::iterator iter = indices.begin(); iter != indices.end(); ++iter) {                *iter = leaf_count;                leaf_count++;        }        root = new TreeNode();        root->indices = indices;        root->height = this->height - 1;        root->index = -1;        leaf_count = 0;        this->dimension = (*data)[0].size();        queue<TreeNode *> q;        q.push(this->root);        while (!q.empty()) {                TreeNode *node = q.front();                if (node->height == 0 || node->indices.size() < this->min_items) {                        node->index = leaf_count;                        leaf_count++;                } else {                        this->splitF(node);                        vector<float> wx(node->indices.size());                        for (int i = 0; i < node->indices.size(); i++) {                                wx[i] = this->dot((*this->data)[node->indices[i]], node->w);                        }                        float low_percent = 0.5 - this->spill / 2;                        float high_percent = 0.5 + this->spill / 2;                        node->thresholds[0] = this->find_percentile(low_percent, wx);                        node->thresholds[1] = this->find_percentile(high_percent, wx);                        TreeNode *left = new TreeNode();                        TreeNode *right = new TreeNode();                        node->left = left;                        node->right = right;                        left->height = node->height - 1;                        right->height = node->height - 1;                        left->index = -1;                        right->index = -1;                        for (int i = 0; i < node->indices.size(); i++) {                                if (wx[i] <= node->thresholds[1])                                        left->indices.push_back(node->indices[i]);                                if (wx[i] >= node->thresholds[0])                                        right->indices.push_back(node->indices[i]);                        }                        q.push(left);                        q.push(right);                }                q.pop();        }        //      this->save_rpTree(rptree_file);}