DCT and PCA Based Method for Shape from Focus
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
Depth Estimation by Finding Best Focused Points Using Line Fitting
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
3D Shape from Focus and Depth Map Computation Using Steerable Filters
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Comparison of polymers: a new application of shape from focus
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Shape from focus using fast discrete curvelet transform
Pattern Recognition
Optimal depth estimation by combining focus measures using genetic programming
Information Sciences: an International Journal
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Depth estimation is an active area of research for 3-dimensional (3D) shape recovery. In this paper, we present a passive depth estimation method. Since the 3-dimensional (3D) cameras currently available are quite expensive, we propose the passive method as a means to decrease the high cost associated with 3D cameras. Our algorithm is based on the 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 yields good results when it is tested with several 3D objects.