| Class | Description |
|---|---|
| Clustering |
A simple greedy clustering algorithm which puts windows in the same cluster
if they are close to each other, and combines clusters if they are close
the goal is to find a set of windows which all represent a good location for the object
|
| DetectionResult |
This state class holds the results of
DetectorCascade.detect(org.openimaj.image.FImage) and
is used primarily to save having to do this work again, this can probably be protected or gone entirley |
| DetectorCascade |
The detector cascade prepares, inititates and controls the 3 underlying
detection steps in the TLD algorithm.
|
| EnsembleClassifier |
The ensemble classifier implements a forest of random binary pixel
comparisons.
|
| IntegralImage |
a 2D double array such that each element is the sum of each
value to the top left of the element,
|
| NNClassifier |
The third and most powerful, but equally most slow parts of the
DetectorCascade. |
| NormalizedPatch |
Defines a intensity normalised patch extracted from an image.
|
| ScaleIndexRectangle |
A rectangle that knows which scale index it belongs to
|
| VarianceFilter |
The variance filter forms the first step of the
DetectorCascade.detect(FImage). |