<p>Template class for 2D points specified by its coordinates <em>x</em> and <em>y</em>. An instance of the class is interchangeable with C structures,

<p>Template class for a 4-element vector derived from Vec.</p> <p>template<typename _Tp> class Scalar_ : public Vec<_Tp, 4> {... }; <code></p> <p>//

<p>OpenCV C++ n-dimensional dense array class</p> <p>class CV_EXPORTS Mat <code></p> <p>// C++ code:</p> <p>public:</p> <p>//... a lot of methods

<p>This is a base class for all more or less complex algorithms in OpenCV, especially for classes of algorithms, for which there can be multiple imple

<p>Base class for background/foreground segmentation.</p> <p>class BackgroundSubtractor : public Algorithm <code></p> <p>// C++ code:</p> <p>publi

<p>Gaussian Mixture-based Background/Foreground Segmentation Algorithm.</p> <p>The class implements the algorithm described in P. KadewTraKuPong and

Basic implementation of LoaderCallbackInterface.

This is a basic class, implementing the interaction with Camera and OpenCV library. The main responsibility of it - is to control when camera can be e

<p>Cascade classifier class for object detection.</p> @see <a href="http://docs.opencv.org/modules/objdetect/doc/cascade_classification.html#cascadec

<p>MLP model.</p> <p>Unlike many other models in ML that are constructed and trained at once, in the MLP model these steps are separated. First, a ne

<p>Parameters of the MLP training algorithm. You can initialize the structure by a constructor or the individual parameters can be adjusted after the

<p>Boosted tree classifier derived from "CvStatModel".</p> @see <a href="http://docs.opencv.org/modules/ml/doc/boosting.html#cvboost">org.opencv.ml.C

<p>Boosting training parameters.</p> <p>There is one structure member that you can set directly:</p> <p>Splitting criteria used to choose optimal sp

<p>The class implements a decision tree as described in the beginning of this section.</p> @see <a href="http://docs.opencv.org/modules/ml/doc/decisi

<p>The structure contains all the decision tree training parameters. You can initialize it by default constructor and then override any parameters dir

<p>The class implements the Extremely randomized trees algorithm. <code>CvERTrees</code> is inherited from "CvRTrees" and has the same interface, so s

<p>The class implements the Gradient boosted tree model as described in the beginning of this section.</p> @see <a href="http://docs.opencv.org/modul

<p>GBT training parameters.</p> <p>The structure contains parameters for each single decision tree in the ensemble, as well as the whole model charac

<p>The class implements K-Nearest Neighbors model as described in the beginning of this section.</p> @see <a href="http://docs.opencv.org/modules/ml/

<p>Bayes classifier for normally distributed data.</p> @see <a href="http://docs.opencv.org/modules/ml/doc/normal_bayes_classifier.html#cvnormalbayes

<p>The structure represents the logarithmic grid range of statmodel parameters. It is used for optimizing statmodel accuracy by varying model paramete

<p>Training parameters of random trees.</p> <p>The set of training parameters for the forest is a superset of the training parameters for a single tr

<p>The class implements the random forest predictor as described in the beginning of this section.</p> @see <a href="http://docs.opencv.org/modules/m

<p>Support Vector Machines.</p> @see <a href="http://docs.opencv.org/modules/ml/doc/support_vector_machines.html#cvsvm">org.opencv.ml.CvSVM : public

<p>SVM training parameters.</p> <p>The structure must be initialized and passed to the training method of "CvSVM".</p> @see <a href="http://docs.ope

<p>Base class for statistical models in ML.</p> <p>class CvStatModel <code></p> <p>// C++ code:</p> <p>public:</p> <p>/ CvStatModel(); /</p> <p>

Structure for matching: query descriptor index, train descriptor index, train image index and distance between descriptors.

<p>Abstract base class for computing descriptors for image keypoints.</p> <p>class CV_EXPORTS DescriptorExtractor <code></p> <p>// C++ code:</p> <

<p>Abstract base class for matching keypoint descriptors. It has two groups of match methods: for matching descriptors of an image with another image

<p>The class implements the EM algorithm as described in the beginning of this section. It is inherited from "Algorithm".</p> @see <a href="http://do

<p>All face recognition models in OpenCV are derived from the abstract base class "FaceRecognizer", which provides a unified access to all face recong

<p>Abstract base class for 2D image feature detectors.</p> <p>class CV_EXPORTS FeatureDetector <code></p> <p>// C++ code:</p> <p>public:</p> <p>v

<p>Abstract interface for extracting and matching a keypoint descriptor. There are also "DescriptorExtractor" and "DescriptorMatcher" for these purpos

Installation callback interface.

This class is an implementation of the Bridge View between OpenCV and Java Camera. This class relays on the functionality available in base class and

<p>Kalman filter class.</p> <p>The class implements a standard Kalman filter http://en.wikipedia.org/wiki/Kalman_filter, [Welch95]. However, you can

<p>Data structure for salient point detectors.</p> <p>coordinates of the keypoint</p> <p>diameter of the meaningful keypoint neighborhood <code></p>

Interface for callback object in case of asynchronous initialization of OpenCV.

This class is an implementation of a bridge between SurfaceView and native OpenCV camera. Due to the big amount of work done, by the base class this c

Class provides a Java interface for OpenCV Engine Service. It's synchronous with native OpenCVEngine class.

Helper class provides common initialization methods for OpenCV library.

<p>Template class for 3D points specified by its coordinates <em>x</em>, <em>y</em> and <em>z</em>. An instance of the class is interchangeable with t

This class is a controller for puzzle game. It converts the image from Camera into the shuffled image