Joe Verbout
opencv on mbed
BOWImgDescriptorExtractor Class Reference
[Object Categorization]
Class to compute an image descriptor using the *bag of visual words*. More...
#include <features2d.hpp>
Public Member Functions | |
| CV_WRAP | BOWImgDescriptorExtractor (const Ptr< DescriptorExtractor > &dextractor, const Ptr< DescriptorMatcher > &dmatcher) |
| The constructor. | |
| BOWImgDescriptorExtractor (const Ptr< DescriptorMatcher > &dmatcher) | |
| CV_WRAP void | setVocabulary (const Mat &vocabulary) |
| Sets a visual vocabulary. | |
| CV_WRAP const Mat & | getVocabulary () const |
| Returns the set vocabulary. | |
| void | compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray imgDescriptor, std::vector< std::vector< int > > *pointIdxsOfClusters=0, Mat *descriptors=0) |
| Computes an image descriptor using the set visual vocabulary. | |
| void | compute (InputArray keypointDescriptors, OutputArray imgDescriptor, std::vector< std::vector< int > > *pointIdxsOfClusters=0) |
| This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. | |
| CV_WRAP int | descriptorSize () const |
| Returns an image descriptor size if the vocabulary is set. | |
| CV_WRAP int | descriptorType () const |
| Returns an image descriptor type. | |
Detailed Description
Class to compute an image descriptor using the *bag of visual words*.
Such a computation consists of the following steps:
1. Compute descriptors for a given image and its keypoints set. 2. Find the nearest visual words from the vocabulary for each keypoint descriptor. 3. Compute the bag-of-words image descriptor as is a normalized histogram of vocabulary words encountered in the image. The i-th bin of the histogram is a frequency of i-th word of the vocabulary in the given image.
Definition at line 1252 of file features2d.hpp.
Constructor & Destructor Documentation
| CV_WRAP BOWImgDescriptorExtractor | ( | const Ptr< DescriptorExtractor > & | dextractor, |
| const Ptr< DescriptorMatcher > & | dmatcher | ||
| ) |
The constructor.
- Parameters:
-
dextractor Descriptor extractor that is used to compute descriptors for an input image and its keypoints. dmatcher Descriptor matcher that is used to find the nearest word of the trained vocabulary for each keypoint descriptor of the image.
| BOWImgDescriptorExtractor | ( | const Ptr< DescriptorMatcher > & | dmatcher ) |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Member Function Documentation
| void compute | ( | InputArray | image, |
| std::vector< KeyPoint > & | keypoints, | ||
| OutputArray | imgDescriptor, | ||
| std::vector< std::vector< int > > * | pointIdxsOfClusters = 0, |
||
| Mat * | descriptors = 0 |
||
| ) |
Computes an image descriptor using the set visual vocabulary.
- Parameters:
-
image Image, for which the descriptor is computed. keypoints Keypoints detected in the input image. imgDescriptor Computed output image descriptor. pointIdxsOfClusters Indices of keypoints that belong to the cluster. This means that pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster (word of vocabulary) returned if it is non-zero. descriptors Descriptors of the image keypoints that are returned if they are non-zero.
| void compute | ( | InputArray | keypointDescriptors, |
| OutputArray | imgDescriptor, | ||
| std::vector< std::vector< int > > * | pointIdxsOfClusters = 0 |
||
| ) |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters:
-
keypointDescriptors Computed descriptors to match with vocabulary. imgDescriptor Computed output image descriptor. pointIdxsOfClusters Indices of keypoints that belong to the cluster. This means that pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster (word of vocabulary) returned if it is non-zero.
| CV_WRAP int descriptorSize | ( | ) | const |
Returns an image descriptor size if the vocabulary is set.
Otherwise, it returns 0.
| CV_WRAP int descriptorType | ( | ) | const |
Returns an image descriptor type.
| CV_WRAP const Mat& getVocabulary | ( | ) | const |
Returns the set vocabulary.
| CV_WRAP void setVocabulary | ( | const Mat & | vocabulary ) |
Sets a visual vocabulary.
- Parameters:
-
vocabulary Vocabulary (can be trained using the inheritor of BOWTrainer ). Each row of the vocabulary is a visual word (cluster center).
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