Documentation of 'boofcv.factory.tracker.FactoryTrackerObjectQuad' Java class
FactoryTrackerObjectQuad
boofcv.factory.tracker

Class FactoryTrackerObjectQuad



  • public class FactoryTrackerObjectQuad
    extends java.lang.Object
    Factory for implementations of TrackerObjectQuad, a high level interface for tracking user specified objects inside video sequences. As usual, the high level interface makes it easier to use these algorithms at the expensive of algorithm specific features.
    • Constructor Detail

      • FactoryTrackerObjectQuad

        public FactoryTrackerObjectQuad()
    • Method Detail

      • sparseFlow

        public static <T extends ImageGray,D extends ImageGrayTrackerObjectQuad<T> sparseFlow(SfotConfig config,
                                                                                                java.lang.Class<T> imageType,
                                                                                                java.lang.Class<D> derivType)
        Create an instance of Sparse Flow Object Tracker for the TrackerObjectQuad interface.
        Type Parameters:
        T - Image input type
        D - Image derivative type. Null for default.
        Parameters:
        config - Configuration for the tracker, Null for default.
        Returns:
        TrackerObjectQuad
      • meanShiftLikelihood

        public static <T extends ImageBaseTrackerObjectQuad<T> meanShiftLikelihood(int maxIterations,
                                                                                     int numBins,
                                                                                     double maxPixelValue,
                                                                                     MeanShiftLikelihoodType modelType,
                                                                                     ImageType<T> imageType)
        Very basic and very fast implementation of mean-shift which uses a fixed sized rectangle for its region. Works best when the target is composed of a single color.
        Parameters:
        maxIterations - Maximum number of mean-shift iterations. Try 30.
        numBins - Number of bins in the histogram color model. Try 5.
        maxPixelValue - Maximum number of pixel values. For 8-bit images this will be 256
        modelType - Type of color model used.
        imageType - Type of image
        Returns:
        TrackerObjectQuad based on TrackerMeanShiftLikelihood.
        See Also:
        TrackerMeanShiftLikelihood
      • meanShiftComaniciu2003

        public static <T extends ImageBaseTrackerObjectQuad<T> meanShiftComaniciu2003(ConfigComaniciu2003 config,
                                                                                        ImageType<T> imageType)
        Implementation of mean-shift which matches the histogram and can handle targets composed of multiple colors. The tracker can also be configured to estimate gradual changes in scale. The track region is composed of a rotated rectangle.
        Type Parameters:
        T - Image type
        Parameters:
        config - Tracker configuration
        Returns:
        TrackerObjectQuad based on Comaniciu2003
        See Also:
        TrackerMeanShiftComaniciu2003
      • circulant

        public static <T extends ImageGrayTrackerObjectQuad<T> circulant(ConfigCirculantTracker config,
                                                                           java.lang.Class<T> imageType)
        Creates the Circulant feature tracker. Texture based tracker which uses the theory of circulant matrices, Discrete Fourier Transform (DCF), and linear classifiers to track a target. Fixed sized rectangular target and only estimates translation. Can't detect when it loses track or re-aquire track.
        Parameters:
        config - Configuration
        Returns:
        CirculantTracker
        See Also:
        CirculantTracker

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