Dental Smile Simulation with Depth-Aware Color Accuracy

The patent introduces depth maps as an intermediary element between the input image and the final simulated output. The depth map encodes three-dimensional spatial information about tooth positions and orientations, which serves as a mediator to guide the GAN in generating accurate coloration. This intermediary allows the system to transfer color properties from the input image to the simulated output while maintaining spatial accuracy, resolving the contradiction between simple generation processes and accurate coloration.

The patent transforms the input image into a depth map by analyzing pixel intensity values and determining depth parameters for different regions. This parameter transformation converts two-dimensional image data into three-dimensional spatial information, which is then used to guide the coloration process. By changing parameters from simple pixel values to depth-encoded spatial coordinates, the system achieves accurate coloration while maintaining computational efficiency.

The patent segments the image processing into distinct stages: depth map generation, blur function application, and GAN-based image synthesis. By dividing the computational task into separate modules, each handling a specific aspect of the problem, the system achieves accurate color transitions without requiring all computational resources to be engaged simultaneously. This segmentation allows for optimized resource allocation and reduces peak computational power requirements.

The patent performs preliminary processing by generating depth maps and determining blur functions before the main GAN-based image synthesis. This preliminary action prepares the spatial and color transition parameters in advance, allowing the GAN to focus solely on generating realistic tooth coloration and textures. By performing preparatory computations beforehand, the system reduces the computational burden during the final image generation phase.