Documentation of 'boofcv.alg.sfm.d3.VisOdomQuadPnP' Java class
VisOdomQuadPnP
boofcv.alg.sfm.d3

Class VisOdomQuadPnP<T extends ImageGray,TD extends TupleDesc>



  • public class VisOdomQuadPnP<T extends ImageGray,TD extends TupleDesc>
    extends java.lang.Object
    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 algorithms. These require that each image feature as its 3D coordinate estimated. After a feature is associated between a stereo pair its 3D location is also estimated using triangulation. Iterative refinement can then be applied after motion has been estimated. Inside the code each camera is some times referred to by number. 0 = left camera previous frame. 1 = right camera previous frame. 2 = left camera current frame. 3 = right camera current frame. Estimated motion is relative to left camera.
    • Method Detail

      • 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 Se3_F64 getLeftToWorld()

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