A method of converting two-dimensional images to three-dimensional images, comprising: receiving a sequence of images; processing at least one image of the sequence of images using a range estimation algorithm to create a range to target map of an image scene by exploiting edge information in conjunction with spatial and temporal differences that occur during image acquisition, wherein the range estimation algorithm generates a map of range to target values of objects in the at least one image by measuring the spatial and temporal changes that occur between the current frame and the frame prior to the current frame on a per pixel basis and each range estimation is then weighted against an initial guess at scene topography, wherein said processing further comprises analysing each frame to map objects in relation to their position in the frame and with respect to other objects in the frame, breaking the frame into several views and subsequently breaking the frame into several sub-regions where the analysing iterates such that a range estimation measurement for each object can be computed; creating n-number of unique views from the range to target map for two or more left and right image pairs of the image scene at a same instance of time, each unique view being calculated to generate a different camera perspective of the image scene, wherein n is greater than or equal to two; weaving the n-number of unique views together on a sub-pixel basis to form an interleaved image pattern to display the two or more left and right image pairs at the same instance of time on a display screen configured with a lenticular lens , the weaving being based on a physical geometry of the lenticular lens and the display screen; and interpolating the two or more left and right image pairs across each lenticule of a plurality of lenticules of the lenticular lens to display the interleaved image pattern as an auto-stereoscopic video sequence. receiving a sequence of images; processing at least one image of the sequence of images using a range estimation algorithm to create a range to target map of an image scene by exploiting edge information in conjunction with spatial and temporal differences that occur during image acquisition, wherein the range estimation algorithm generates a map of range to target values of objects in the at least one image by measuring the spatial and temporal changes that occur between the current frame and the frame prior to the current frame on a per pixel basis and each range estimation is then weighted against an initial guess at scene topography, wherein said processing further comprises analysing each frame to map objects in relation to their position in the frame and with respect to other objects in the frame, breaking the frame into several views and subsequently breaking the frame into several sub-regions where the analysing iterates such that a range estimation measurement for each object can be computed; creating n-number of unique views from the range to target map for two or more left and right image pairs of the image scene at a same instance of time, each unique view being calculated to generate a different camera perspective of the image scene, wherein n is greater than or equal to two; weaving the n-number of unique views together on a sub-pixel basis to form an interleaved image pattern to display the two or more left and right image pairs at the same instance of time on a display screen configured with a lenticular lens , the weaving being based on a physical geometry of the lenticular lens and the display screen; and interpolating the two or more left and right image pairs across each lenticule of a plurality of lenticules of the lenticular lens to display the interleaved image pattern as an auto-stereoscopic video sequence. <EOS>