A method for estimating if an object is viewable by both a first camera and a user where a first camera and a second camera respective center lines of field of view may not be on the same line, wherein the distance of the user from the second camera is estimated, by estimating human head size, the proportion between the horizontal distance HD and second camera field of view γ where horizontal distance HD is measured by a number of pixels, wherein the second camera has a horizontal angular opening of a total of γ degrees, wherein estimating an angular deviation α between the second center line of sight and an imaginary line from the second camera to the detected human face is based on the equation α = γ * (DEV/HD), wherein DEV is the detected face location's horizontal deviation from the center of the image, HD is the total horizontal distance of the captured image, and γ is the horizontal angular field of view of the second camera; wherein estimating an angular deviation β between the imaginary line from the second camera to the detected face and the human face gaze of head pose direction by applying a human gaze direction estimation algorithm on the captured image is using eye detection or eye tracking or head pose estimation; wherein the coordinates of origin of user field of view, defined as the user coordinates system may be determined relative to the second camera coordinates system, are based on the estimated distance and the estimated angle β, wherein a transformation matrix may be constructed for transforming from the user coordinates system to the second camera coordinates system, wherein the estimated distance may be used to construct a translation matrix, and the user gaze is used to construct a rotation matrix, and the two matrices are combined to form a transformation matrix, where the transformation matrices to and from the first camera and to the second camera are calculated from the known distances and angles of the two cameras, whether or not they are integrated in a single device, wherein the coordinates of every point inside the user field of view, given a cone to represent the 3D field of view, is calculated using second camera coordinate system, wherein a point located in the first camera coordinate system is transformed to the user gaze coordinate system, where the first camera properties are used to estimate the field of view coordinates that are inside the Depth Of Field, in order to estimate the object size and distance from the first camera, same as head location is estimated by second camera. wherein the distance of the user from the second camera is estimated, by estimating human head size, the proportion between the horizontal distance HD and second camera field of view γ where horizontal distance HD is measured by a number of pixels, wherein the second camera has a horizontal angular opening of a total of γ degrees, wherein estimating an angular deviation α between the second center line of sight and an imaginary line from the second camera to the detected human face is based on the equation α = γ * (DEV/HD), wherein DEV is the detected face location's horizontal deviation from the center of the image, HD is the total horizontal distance of the captured image, and γ is the horizontal angular field of view of the second camera; wherein estimating an angular deviation β between the imaginary line from the second camera to the detected face and the human face gaze of head pose direction by applying a human gaze direction estimation algorithm on the captured image is using eye detection or eye tracking or head pose estimation; wherein the coordinates of origin of user field of view, defined as the user coordinates system may be determined relative to the second camera coordinates system, are based on the estimated distance and the estimated angle β, wherein a transformation matrix may be constructed for transforming from the user coordinates system to the second camera coordinates system, wherein the estimated distance may be used to construct a translation matrix, and the user gaze is used to construct a rotation matrix, and the two matrices are combined to form a transformation matrix, where the transformation matrices to and from the first camera and to the second camera are calculated from the known distances and angles of the two cameras, whether or not they are integrated in a single device, wherein the coordinates of every point inside the user field of view, given a cone to represent the 3D field of view, is calculated using second camera coordinate system, wherein a point located in the first camera coordinate system is transformed to the user gaze coordinate system, where the first camera properties are used to estimate the field of view coordinates that are inside the Depth Of Field, in order to estimate the object size and distance from the first camera, same as head location is estimated by second camera.