Abstract
Estimating the relative 3D shape of the object is an important research topic in the area of computer vision, and is being used in a wide range of applications such as robot vision, computer games, animations, broadcast, and many more. Several active and passive methods have been proposed for recovering 3-D shape of the objects from their 2-D images. Passive methods like Shape from Focus (SFF), Shape from Defocus (SFD), Shape from Shading (SFS) etc are cheap and more effective, requiring stack of images by a single camera. In this paper, we have developed a simple and fast algorithm for SFF to calculate depth. The pixel intensities in the image sequences are modified by subtracting the maximum of first or last frame in the image sequence. A low pass filter is applied on these modified values to eliminate the noise. The proposed algorithm is fast and precise, as compared to earlier SFF methods.
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Mannan, S.M., Mutahira, H., Choi, TS. (2009). Shape Recovery by Focus Based Methods Using Low Pass Filter. In: Ślęzak, D., Kim, Th., Chang, A.CC., Vasilakos, T., Li, M., Sakurai, K. (eds) Communication and Networking. FGCN 2009. Communications in Computer and Information Science, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10844-0_62
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DOI: https://doi.org/10.1007/978-3-642-10844-0_62
Publisher Name: Springer, Berlin, Heidelberg
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