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  • Küçük Resim
    Yayın
    Co-registration of 3d point clouds by using an errors-in-variables model
    (Copernicus Gesellschaft MBH, 2012-08-25) Aydar, Umut; Altan, Mehmet Orhan; Akyılmaz, Orhan; Akça, Mehmet Devrim
    Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D least squares (LS) matching methods as well. In most of the co-registration methods, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values. This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a new method where the stochastic properties of both (template and search) surfaces are considered under an errors-in-variables (EIV) model. The experiments have been carried out using a close range laser scanning data set and the results of the conventional and EIV types of the ICP matching methods have been compared.
  • Küçük Resim
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    Total least squares registration of 3D surfaces
    (Copernicus GmbH, 2013-10-16) Aydar, Umut; Akça, Mehmet Devrim; Altan, Mehmet Orhan; Akyılmaz, Orhan
    Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of coregistration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In computer vision and photogrammetry domain one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D Least Squares (LS) matching methods as well (Gruen and Akca, 2005). The co-registration methods commonly use the least squares (LS) estimation method in which the unknown transformation parameters of the (floating) search surface is functionally related to the observation of the (fixed) template surface. Here, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values of the search surface. . This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a method where the stochastic properties of both the observations and the parameters are considered under an errors-in-variables (EIV) model. The experiments have been carried out using diverse laser scanning data sets and the results of EIV with the ICP and the conventional LS matching methods have been compared.
  • Küçük Resim
    Yayın
    A numerical approach for the design of matching networks consisting of brune sections based on fujisawa constraints
    (IEEE, 2018) Yıldız, Serkan; Aksen, Ahmet; Yarman, Bekir Sıddık Binboğa
    In this study, the realization problem of matching network consisting of Brune sections is investigated. In the synthesis of a general impedance function with finite transmission zeros, each transmission zero extraction results in a Brune section involving a negative reactive element. Although coupled inductances can be used to remove negative elements, a direct mutual coupling free ladder design is aimed by properly incorporating the mid-shunt ladder realizability conditions of Fujisawa. For this purpose, impedance based Real Frequency Technique (RFT) is used to construct realizable impedance function and Fujisawa synthesis procedure is applied for mid-shunt ladder realization. An illustrative matching network design example is presented.
  • Küçük Resim
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    Hierarchical b-Matching
    (Springer Science and Business Media Deutschland GmbH, 2021) Emek, Yuval; Kutten, Shay; Shalom, Mordechai; Zaks, Shmuel
    A matching of a graph is a subset of edges no two of which share a common vertex, and a maximum matching is a matching of maximum cardinality. In a b-matching every vertex v has an associated bound bv, and a maximum b-matching is a maximum set of edges, such that every vertex v appears in at most bv of them. We study an extension of this problem, termed Hierarchical b-Matching. In this extension, the vertices are arranged in a hierarchical manner. At the first level the vertices are partitioned into disjoint subsets, with a given bound for each subset. At the second level the set of these subsets is again partitioned into disjoint subsets, with a given bound for each subset, and so on. We seek for a maximum set of edges, that obey all bounds (that is, no vertex v participates in more than bv edges, then all the vertices in one subset do not participate in more that subset’s bound of edges, and so on hierarchically). This is a sub-problem of the matroid matching problem which is NP -hard in general. It corresponds to the special case where the matroid is restricted to be laminar and the weights are unity. A pseudo-polynomial algorithm for the weighted laminar matroid matching problem is presented in [8]. We propose a polynomial-time algorithm for Hierarchical b-matching, i.e. the unweighted laminar matroid matching problem, and discuss how our techniques can possibly be generalized to the weighted case.