A method of estimating an orientation of a camera relative to a surface, wherein a camera coordinate system is defined and a normal vector normal to the surface is represented by three components in the camera coordinate system, the method comprising: providing a first image and a subsequent second image captured by the camera; selecting a first point from the first image and a second point from the second image, wherein the first and second points represent the same object; and defining a first optical flow vector connecting the first point and the second point, characterized in that the method further comprises: carrying out a first estimation step comprising estimating two components of the normal vector in the camera coordinate system by using the first optical flow vector and restricting parameter space to only the two components of the normal vector by initially assuming a fixed value for the remaining third component of the normal vector, wherein a linear equation system derived from a homography matrix that represents a projective transformation between the first image and the second image is provided and the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system; determining the orientation of the camera relative to the surface using the results of the first estimation step; and carrying out a second estimation step subsequent to the first estimation step that comprises estimating the two components of the normal vector in the camera coordinate system again by using the first optical flow vector and setting the component of the normal vector neglected in the first estimation step to a value derived from the first estimation step, wherein the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system and the orientation of the camera relative to the surface is determined by using the components of the normal vector estimated in the second estimation step, and wherein in the second estimation step the component of the normal vector neglected in the first estimation step is set to the inverse of the amount of the normal vector derived from the first estimation step. providing a first image and a subsequent second image captured by the camera; selecting a first point from the first image and a second point from the second image, wherein the first and second points represent the same object; and defining a first optical flow vector connecting the first point and the second point, characterized in that the method further comprises: carrying out a first estimation step comprising estimating two components of the normal vector in the camera coordinate system by using the first optical flow vector and restricting parameter space to only the two components of the normal vector by initially assuming a fixed value for the remaining third component of the normal vector, wherein a linear equation system derived from a homography matrix that represents a projective transformation between the first image and the second image is provided and the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system; determining the orientation of the camera relative to the surface using the results of the first estimation step; and carrying out a second estimation step subsequent to the first estimation step that comprises estimating the two components of the normal vector in the camera coordinate system again by using the first optical flow vector and setting the component of the normal vector neglected in the first estimation step to a value derived from the first estimation step, wherein the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system and the orientation of the camera relative to the surface is determined by using the components of the normal vector estimated in the second estimation step, and carrying out a first estimation step comprising estimating two components of the normal vector in the camera coordinate system by using the first optical flow vector and restricting parameter space to only the two components of the normal vector by initially assuming a fixed value for the remaining third component of the normal vector, wherein a linear equation system derived from a homography matrix that represents a projective transformation between the first image and the second image is provided and the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system; determining the orientation of the camera relative to the surface using the results of the first estimation step; and carrying out a second estimation step subsequent to the first estimation step that comprises estimating the two components of the normal vector in the camera coordinate system again by using the first optical flow vector and setting the component of the normal vector neglected in the first estimation step to a value derived from the first estimation step, wherein the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system and the orientation of the camera relative to the surface is determined by using the components of the normal vector estimated in the second estimation step, and wherein in the second estimation step the component of the normal vector neglected in the first estimation step is set to the inverse of the amount of the normal vector derived from the first estimation step.