* Constructor. */

* Constructor. * @param n Size of the interval from which to generate * @return */

Default cosntructor */

Calculate probability value: */

Default constructor which creates an object that can be

Default constructor which creates an object that can be

Refer to external data. This does NOT take ownership of the supplied IplImage.

Refer to external data. This does NOT take ownership of the supplied IplImage.

WidthStep is the number of bytes to go to the pixel with the next y coord

* [Callback for when User Lost]: This code executed every time an existing * user is no longer visible to UserGenerator node for more than 10secs

* [Callback for when New User Detected]: This code is executed every time a new user is detected by UserGenerator node * @param generator UserGenera

Add a possible candidate to the best neighbors * @param dist distance for that neighbor * @param index index of that neighbor */

Add a possible candidate to the best neighbors * @param dist distance for that neighbor * @param index index of that neighbor */

FabMap2 builds the inverted index and requires an additional training/test add function

address

! Aligns buffer size by the certain number of bytes This small inline function aligns a buffer size by the certian number of bytes by enlarging i

Blend color images 'image1' and 'image2' using an 8-bit alpha-blending mask channel. Equivalent to this operation on each pixel: imageOut = image1 * (

Blend color images 'image1' and 'image2' using an 8-bit alpha-blending mask channel. Equivalent to this operation on each pixel: imageOut = image1 * (

* Builds the index */

* Builds the index */

* \brief Builds the index */

* Builds the index */

* Builds the index */

* Chooses the initial centers in the k-means using Gonzales' algorithm * so that the centers are spaced apart from each other. * * Para

* Chooses the initial centers in the k-means using Gonzales' algorithm * so that the centers are spaced apart from each other. * * Para

* Chooses the initial centers in the k-means using the algorithm * proposed in the KMeans++ paper: * Arthur, David; Vassilvitskii, Sergei -

* Chooses the initial centers in the k-means using the algorithm * proposed in the KMeans++ paper: * Arthur, David; Vassilvitskii, Sergei -

* Chooses the initial centers in the k-means clustering in a random manner. * * Params: * k = number of centers * vecs = t