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Item type:Publication, Access status: without files , Variance and symmetrical-based approach for optimal alignment of 3D model(2018-10); ; The concept of building 3D models, known as 3D reconstruction, already exists since the last few decades. However, by manually aligning the objects during acquisition phase does not guarantee that the output, the 3D models, will be perfectly aligned with the computer's world coordinate system. It mainly happens because in real world it is quite challenging to get perfect measurements, especially for the irregular objects. In this paper we address this problem by proposing a method to be used on the post processing phase of the 3D reconstruction process. The method is based on the variance and symmetricity of the object's point cloud which is acquired during acquisition. For the evaluation, we applied and evaluated the proposed method to both synthetic and reconstructed 3D models. The results are significant and show that the method capable of aligning the models to a fine resolution of 1' (one minute) angle.Publicationtype: Conference Paper132 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , SIFT-EST - a SIFT-based feature matching algorithm using homography estimationIn this paper, a new feature matching algorithm is proposed and evaluated. This method makes use of features that are extracted by SIFT and aims at reducing the processing time of the matching phase of SIFT. The idea behind this method is to use the information obtained from already detected matches to restrict the range of possible correspondences in the subsequent matching attempts. For this purpose, a few initial matches are used to estimate the homography that relates the two images. Based on this homography, the estimated location of the features of the reference image after transformation to the test image can be specified. This information is used to specify a small set of possible matches for each reference feature based on their distance to the estimated location. The restriction of possible matches leads to a reduction of processing time since the quadratic complexity of the one-to-one matching is undermined. Due to the restrictions of 2D homographies, this method can only be applied to images that are related by pure-rotational transformations or images of planar object.Publicationtype: Conference Paper96 132 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , 101 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A study of Kruppa’s equation for camera self-calibrationIn this paper we discuss the Kruppa’s equation, which is widely known as the first camera self-calibration method. The classical and the simplified version of the method are of our interest. We have analyzed it based on how it is derived. As Kruppa’s equation works based on the image of the absolute conic, which is an imaginary conic, we have found that the use of circular points at infinity was missed in the classical Kruppa’s in generating the imaginary conic. We have pointed out that the concept of degenerate point conic in deriving the simplified version is one of the reasons of degeneracy. Other than that, we also found some other inaccuracies of the derivation. For the future use as well as the improvement of the method, we have proposed possible solutions for it.Publicationtype: Conference Paper32