Combining Focus Measures for Three Dimensional Shape Estimation Using Genetic Programming
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- @InCollection{Mahmood:2012:dm3dia,
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author = "Muhammad Tariq Mahmood and Tae-Sun Choi",
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title = "Combining Focus Measures for Three Dimensional Shape
Estimation Using Genetic Programming",
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booktitle = "Depth Map and {3D} Imaging Applications: Algorithms
and Technologies",
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publisher = "IGI Global",
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year = "2012",
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editor = "Aamir Saeed Malik and Tae Sun Choi and Humaira Nisar",
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chapter = "11",
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pages = "209--228",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "9781613503263",
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DOI = "doi:10.4018/978-1-61350-326-3.ch011",
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abstract = "Three-dimensional (3D) shape reconstruction is a
fundamental problem in machine vision applications.
Shape from focus (SFF) is one of the passive optical
methods for 3D shape recovery, which uses degree of
focus as a cue to estimate 3D shape. In this approach,
usually a single focus measure operator is applied to
measure the focus quality of each pixel in image
sequence. However, the applicability of a single focus
measure is limited to estimate accurately the depth map
for diverse type of real objects. To address this
problem, we introduce the development of optimal
composite depth (OCD) function through genetic
programming (GP) for accurate depth estimation. The OCD
function is developed through optimally combining the
primary information extracted using one (homogeneous
features) or more focus measures (heterogeneous
features). The genetically developed composite function
is then used to compute the optimal depth map of
objects. The performance of this function is
investigated using both synthetic and real world image
sequences. Experimental results demonstrate that the
proposed estimator is more accurate than existing SFF
methods. Further, it is found that heterogeneous
function is more effective than homogeneous function.",
- }
Genetic Programming entries for
Muhammad Tariq Mahmood
Tae Sun Choi
Citations