Package boofcv.alg.sfm.d3

Class VisOdomStereoQuadPnP<T extends boofcv.struct.image.ImageGray<T>,​TD extends boofcv.struct.feature.TupleDesc>

  • All Implemented Interfaces:
    org.ddogleg.struct.VerbosePrint
    public class VisOdomStereoQuadPnP<T extends boofcv.struct.image.ImageGray<T>,​TD extends boofcv.struct.feature.TupleDesc>
extends java.lang.Object
implements org.ddogleg.struct.VerbosePrint
    Stereo visual odometry algorithm which associates image features across two stereo pairs for a total of four images. Image features are first matched between left and right images while applying epipolar constraints. Then the two more recent sets of stereo images are associated with each other in a left to left and right to right fashion. Features which are consistently matched across all four images are saved in a list. RANSAC is then used to remove false positives and estimate camera motion using a PnP type algorithm. Motion is estimated using PNP with RANSAC. The initial 3D location of a feature is found using the stereo pair in the key frame. After the initial motion is found it can optionally be refined. Now that the location of all four cameras is known points are triangulated again using all four views. Then the optional final step is to run bundle adjustment. Features are uniquely tracked from one image to the next. This allows the refined 3D location of each feature to benefit future frames instead of being lost. However, due to the nature of the DDA image tracker, losing track is quite common. The previous stereo pair is referred to as the key frame because it's the reference point that motion is estimated relative to. Inside the code each camera is some times referred to by number. 0 = left camera key frame. 1 = key camera previous frame. 2 = left camera current frame. 3 = right camera current frame.

    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected java.io.PrintStream profileOut  
      protected java.io.PrintStream verbose  

    • Constructor Summary

      Constructors 
      Constructor Description
      VisOdomStereoQuadPnP​(boofcv.abst.feature.detdesc.DetectDescribePoint<T,​TD> detector, boofcv.abst.feature.associate.AssociateDescription<TD> assocF2F, boofcv.abst.feature.associate.AssociateDescription2D<TD> assocL2R, boofcv.abst.geo.Triangulate2ViewsMetric triangulate, org.ddogleg.fitting.modelset.ModelMatcher<georegression.struct.se.Se3_F64,​Stereo2D3D> matcher, org.ddogleg.fitting.modelset.ModelFitter<georegression.struct.se.Se3_F64,​Stereo2D3D> modelRefiner, boofcv.abst.geo.bundle.BundleAdjustment<boofcv.abst.geo.bundle.SceneStructureMetric> bundleAdjustment)
      Specifies internal algorithms

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      georegression.struct.se.Se3_F64 getLeftToWorld()  
      boolean process​(T left, T right)
      Estimates camera egomotion from the stereo pair
      void reset()
      Resets the algorithm into its original state
      void setCalibration​(boofcv.struct.calib.StereoParameters param)
      Sets and saves the stereo camera's calibration
      void setVerbose​(java.io.PrintStream out, java.util.Set<java.lang.String> configuration)  

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • profileOut

        protected java.io.PrintStream profileOut

      • verbose

        protected java.io.PrintStream verbose

    • Constructor Detail

      • VisOdomStereoQuadPnP

        public VisOdomStereoQuadPnP​(boofcv.abst.feature.detdesc.DetectDescribePoint<T,​TD> detector,
                            boofcv.abst.feature.associate.AssociateDescription<TD> assocF2F,
                            boofcv.abst.feature.associate.AssociateDescription2D<TD> assocL2R,
                            boofcv.abst.geo.Triangulate2ViewsMetric triangulate,
                            org.ddogleg.fitting.modelset.ModelMatcher<georegression.struct.se.Se3_F64,​Stereo2D3D> matcher,
                            org.ddogleg.fitting.modelset.ModelFitter<georegression.struct.se.Se3_F64,​Stereo2D3D> modelRefiner,
                            boofcv.abst.geo.bundle.BundleAdjustment<boofcv.abst.geo.bundle.SceneStructureMetric> bundleAdjustment)
        Specifies internal algorithms
        Parameters:
        detector - Estimates image features
        assocF2F - Association algorithm used for left to left and right to right
        assocL2R - Assocation algorithm used for left to right
        triangulate - Used to estimate 3D location of a feature using stereo correspondence
        matcher - Robust model estimation. Often RANSAC
        modelRefiner - Non-linear refinement of motion estimation

    • Method Detail

      • setCalibration

        public void setCalibration​(boofcv.struct.calib.StereoParameters param)
        Sets and saves the stereo camera's calibration

      • reset

        public void reset()
        Resets the algorithm into its original state

      • process

        public boolean process​(T left,
                       T right)
        Estimates camera egomotion from the stereo pair
        Parameters:
        left - Image from left camera
        right - Image from right camera
        Returns:
        true if motion was estimated and false if not

      • getLeftToWorld

        public georegression.struct.se.Se3_F64 getLeftToWorld()

      • setVerbose

        public void setVerbose​(@Nullable
                       java.io.PrintStream out,
                       @Nullable
                       java.util.Set<java.lang.String> configuration)
        Specified by:
        setVerbose in interface org.ddogleg.struct.VerbosePrint