The activation of ancient vessel-fragments is a time consuming but important task for archaeologists. The basis for classification and reconstruction is the profile which is the cross-section of the fragment in the di...
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The activation of ancient vessel-fragments is a time consuming but important task for archaeologists. The basis for classification and reconstruction is the profile which is the cross-section of the fragment in the direction of the rotational axis of symmetry. Hence the position of a fragment (orientation) on a vessel is important. In this work the estimation of the axis of rotation out of range data by using a Hough inspired method is proposed. In order to avoid outliers a robust method for estimation of the axis is used. Classification and reconstruction are performed in a bottom-up manner using a description language, which holds all features of the fragment as primitives and all properties among features as relations. Classification of newly found fragments of unknown type is performed by comparing the description of the new fragment with the description of already classified fragments by completing graph similarity. The sub-graph with the highest similarity is then used to reconstruct the complete vessel out of the fragment.
This paper presents an application of 3D-reconstruction and graph theory in the field of archaeology. The classification and reconstruction of ancient pots and vessels out of fragments (so-called sherds) is an importa...
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This paper presents an application of 3D-reconstruction and graph theory in the field of archaeology. The classification and reconstruction of ancient pots and vessels out of fragments (so-called sherds) is an important aspect of archaeological research work. Up to now this is a time consuming, inaccurate, and subjective task which leads to tons of unclassified fragments in archives. Computer aided classification could help to get a better understanding of ancient cultures, since all data of an excavation would be accessible to the public, not only- selected parts as it is now. We propose a bottom-up strategy to classify fragments. The profile section (which is a section a the fragment in the direction of the rotational axis) is segmented into its primitives (with certain properties like length) and relations among this primitives (like position and curvature of connecting points). These primitives and the relations form a description language, different profiles have different descriptions.
The arrangement of brush strokes is an important criterion in classifying portrait miniatures. In order to detect single brush strokes we used both a model based and a semi-parametric, neural network approach. The per...
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The arrangement of brush strokes is an important criterion in classifying portrait miniatures. In order to detect single brush strokes we used both a model based and a semi-parametric, neural network approach. The performance of both operators is evaluated and compared experimentally.
It is often difficult to attribute works of art to a certain artist. In the case of paintings, radiological methods like X-ray and infra-red diagnosis, digital radiography, computer-tomography, etc. and color analyzes...
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It is often difficult to attribute works of art to a certain artist. In the case of paintings, radiological methods like X-ray and infra-red diagnosis, digital radiography, computer-tomography, etc. and color analyzes are employed to authenticate works of art. But all these methods do not relate certain characteristics of an art work to a specific artist-the artist's personal style. In order to study this personal style, we examine the "structural signature" based on brush strokes in particular in portrait miniatures. A computer-aided classification and recognition system for portrait miniatures is developed, which enables a semi-automatic classification based on brush strokes. A hierarchically structured classification scheme is introduced which separates the classification into three different levels of information: color, shape of region, and structure of brush strokes.
We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equi...
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We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) step...
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We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equi...
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We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equivalently a lower bound on the Mahalanobis distance) on which detection is based. Often, the lower bound of Mahalanobis distance (MD) reaches a preset threshold after computation of only a few eigen-projections. In this case the computation of MD can be immediately terminated. Regardless of the precise value of MD, the detection hypothesis (object from class /spl Omega/ is detected) can be rejected. While provably obtaining results identical to the standard technique, we achieved a two- to three-fold speed-up in face detection experiments on images from the CMU database.
The matching of an object, a region of an image segmentation, to a template is a heavy computation process and is not very robust. We represent an object by a region adjacency graph (RAG) on the top of which a pyramid...
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The matching of an object, a region of an image segmentation, to a template is a heavy computation process and is not very robust. We represent an object by a region adjacency graph (RAG) on the top of which a pyramid...
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The matching of an object, a region of an image segmentation, to a template is a heavy computation process and is not very robust. We represent an object by a region adjacency graph (RAG) on the top of which a pyramid (a decreasing sequence of RAG) is built according to a set of rules, which verify some uniqueness and uniformity properties. The contraction process preserves the structure of the RAG across the pyramid's levels, and the rules are chosen according to the characteristics of the template. By building such a pyramid and then by a top-down process to match all the sub-graphs we have a linear parallel complexity time, with a robust match and a partial match relative to the given set of rules.
The main problem we persue in this paper is the question of when a given path-connectedness in Z2 and Z3 coincides with a topological cormectedness. We answer this question provided the path--connectedness is induced ...
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