code: public static List<Tuple2<Se3_F64,Vector3D_F64>> decomposeHomography( DMatrixRMaj H ) {
  		DecomposeHomography d = new DecomposeHomography();
  
  		d.decompose(H);
  
  		List<Vector3D_F64> solutionsN = d.getSolutionsN();
  		List<Se3_F64> solutionsSe = d.getSolutionsSE();
  
  		List<Tuple2<Se3_F64,Vector3D_F64>> ret = new ArrayList<>();
  		for( int i = 0; i < 4; i++ ) {
  			ret.add(new Tuple2<>(solutionsSe.get(i), solutionsN.get(i)));
  		}
  
  
  		return ret;
  	}
docs: Decomposes a homography matrix that's in Euclidean space (computed from features in normalized image coordinates).
  The homography is defined as H = (R + (1/d)*T*N<sup>T</sup>), where R is a 3x3 rotation matrix,
  d is the distance of the plane, N is the plane's normal (unit vector), T is the translation vector.  If
  the homography is from view 'a' to 'b' then transform (R,T) will be from reference 'a' to 'b'.  Note that the
  returned 'T' is divided by 'd'.
  
  @see DecomposeHomography
  
  @param H Homography in Euclidean space
  @return The set of four possible solutions. First param: motion (R,T).  Second param: plane normal vector.