Estimating 3D-Shape using fuzzy-neuro logic for a 3-dimensional camera

We propose passive methods as a solution to decrease the high cost involved in 3D cameras. The currently available 3-dimensional (3D) cameras are quite expensive because they employ technologies like using three separate lasers to capture XYZ and RGB values, the triangulation method using laser scanner etc. For this purpose, we have developed an approximation technique to calculate depth map for 3D shape recovery. Our algorithm is based on fuzzy-neuro approach. A fuzzy inference system (FIS) is designed and trained using the neural network for the calculation of the depth map. The proposed approximation technique can further be employed in any of the passive methods to acquire depth map for a 3D camera.