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.
We consider the problem of joint motion segmentation and *** algorithm based on region-merging and the Minimum Description Length(MDL) principle is presented *** proposed technique is an unsupervised bottom-up merging...
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We consider the problem of joint motion segmentation and *** algorithm based on region-merging and the Minimum Description Length(MDL) principle is presented *** proposed technique is an unsupervised bottom-up merging method which could be separated into two parts:initial segmentation and further *** error map of motion-compensated prediction error(MCPE) of each region is used to check the motion correlation of the contiguous regions and to obtain the motion vectors of the newly merged *** MDL-based criteria are used to evaluate each possible fusion in further segmentation. The criteria are also used as a test for stopping the merging *** results demonstrate the efficiency of the proposed method.
We consider the problem of joint motion segmentation and estimation. An algorithm based on region-merging and the minimum description length (MDL) principle is presented here. The proposed technique is an unsupervised...
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We consider the problem of joint motion segmentation and estimation. An algorithm based on region-merging and the minimum description length (MDL) principle is presented here. The proposed technique is an unsupervised bottom-up merging method which could be separated into two parts: initial segmentation and further segmentation. The error map of the motion-compensated prediction error (MCPE) of each region is used to check the motion correlation of the contiguous regions and to obtain the motion vectors of the newly merged one. The MDL-based criteria are used to evaluate each possible fusion in further segmentation. The criteria are also used as a test for stopping the merging process. Experimental results demonstrate the efficiency of the proposed method.
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 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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In this paper,a parallel coordinative visual model—The revised Plate Parallel Retrieval Model(Wang 1994) [1]is presented based on the analysis of the global effect of Chinese Characters and the recent neurobiological...
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In this paper,a parallel coordinative visual model—The revised Plate Parallel Retrieval Model(Wang 1994) [1]is presented based on the analysis of the global effect of Chinese Characters and the recent neurobiological researches on the function of neuroglia in learning and *** theory assumes that visual neurons possess the function of memory and retrieval in addition to the commonly recognised function of signal *** supposes all the pixels on the array of a Chinese character are encoded,stored and relieved simultaneously and sychronously by each neuron separately.
In this paper, a parallel coordinative visual model-the revised plate parallel retrieval model (Wang Tianzhen et al, 1994) is presented based on the analysis of the global effect of Chinese characters and the recent n...
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In this paper, a parallel coordinative visual model-the revised plate parallel retrieval model (Wang Tianzhen et al, 1994) is presented based on the analysis of the global effect of Chinese characters and the recent neurobiological research on the function of neuroglia in learning and memory. The theory assumes that visual neurons possess the function of memory and retrieval in addition to the commonly recognised function of signal transformation. It supposes all the pixels in the array of a Chinese character are encoded, stored and retrieved simultaneously and synchronously by each neuron separately. In the model, neuroglia cells play an important role in the integration of the visual signal. The model cannot only satisfactorily explain both the global effect and strokes effect, but can also explain the implicit memory of Chinese characters as well. We have experimented on an SIMD array processor to prove the viability of the PPR algorithm. The results are satisfactory. The model can be extended to general shape vision with some conditions.
Most algorithms for segmenting connected handwritten digit strings are based on the analysis of the foreground pixel distributions and the features on the upper/lower contours of the image. A new approach is presented...
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ISBN:
(纸本)0780344286
Most algorithms for segmenting connected handwritten digit strings are based on the analysis of the foreground pixel distributions and the features on the upper/lower contours of the image. A new approach is presented to segment connected handwritten two-digit strings based on the thinning of background regions. The algorithm first locates several feature points on the background skeleton of the digit image. Possible segmentation paths are then constructed by matching these feature points. With geometric property measures, these segmentation paths are ranked using fuzzy rules generated from a decision-tree approach. Finally, the top ranked segmentation paths are tested one by one by an optimized nearest neighbor classifier until one of these candidates is accepted based on an acceptance criterion. Experimental results on NIST special database 3 show that our approach can achieve a correct classification rate of 92.4% with only 4.7% of digit strings rejected, which compares favorably with the other techniques tested.
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.
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