15040426
3D Surface Reconstruction from Scattered Data Using Moving Least Square Method
This paper presents an efficient implementation of moving least square(MLS) approximation for 3D surface reconstruction. The smoothness of the MLS is mainly determined by the weight function where its support greatly affects the accuracy as well as the computational time in the mixed dense and scattered data. In a point-set, possibly acquired from a 3D scanning device, it is important to determine the support of the weight function adaptively depending on the distribution and shape of the given scatter data. Particulary in case of face data including the very smooth parts, detail parts and some missing parts of hair due to low reflectance, preserving some details while filling the missing parts smoothly is needed. Therefore we present a fast algorithm to estimate the support parameter adaptively by a raster scan method from the quantized integer array of the given data. Some experimental results show that it guarantees the high accuracy and works to fill the missing parts very well.
1712871
Quasi-interpolants Based Multilevel B-Spline Surface Reconstruction from Scattered Data
This paper presents a new fast and local method of 3D surface reconstruction for scattered data. The algorithm makes use of quasi-interpolants to compute the control points from a coarse to fine hierarchy to generate a sequence of bicubic B-spline functions whose sum approaches to the desired interpolation function. Quasi-interpolants gives a procedure for deriving local spline approximation methods where a B-spline coefficient only depends on data points taken from the neighborhood of the support corresponding B-spline. Experimental results demonstrate that high-fidelity reconstruction is possible from a selected set of irregular samples.
13264531
An efficient scattered data approximation using multilevel B-splines based on quasi-interpolants
In this paper, we propose an efficient approximation algorithm using multilevel B-splines based on quasi-interpolants. Multilevel technique uses a coarse to fine hierarchy to generate a sequence of bicubic B-spline functions whose sum approaches the desired interpolation function. To compute a set of control points, quasi-interpolants gives a procedure for deriving local spline approximation methods where a B-spline coefficient only depends on data points taken from the neighborhood of the support corresponding the B-spline. Experimental results show that the smooth surface reconstruction with high accuracy can be obtained from a selected set of scattered or dense irregular samples.
7138459
Comparison of Feature Extraction Techniques for Watermark Synchronization
This paper evaluates feature extraction techniques in aspect of watermark synchronization. Most watermarking algorithms suffer from geometric distortion attacks that desynchronize the location of the inserted watermark. The process of synchronizing the location for watermark insertion and detection is crucial to design robust watermarking. One solution for watermark synchronization is to use features. This paper reviews feature extraction techniques in feature-based watermarking: the Harris corner detector and the Mexican Hat wavelet scale interaction method. We evaluate the scale-invariant keypoint extractor in comparison with others. After feature extraction, the set of triangles is generated by Delaunay tessellation. These triangles are the location for watermarking. Redetection ratio of triangles is measured against geometric distortion attacks and signal processing attacks. Experimental results show that the scale–invariant keypoint extractor is appropriate for robust watermarking.
6458022
Representing the Zoo World and the Traffic World in the language of the Causal Calculator
The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCALC) is a system that answers queries about action domains described in a fragment of that language. The Zoo World and the Traffic World have been proposed by Erik Sandewall in his Logic Modelling Workshop--an environment for communicating axiomatizations of action domains of nontrivial size.The Zoo World consists of several cages and the exterior, gates between them, and animals of several species, including humans. Actions in this domain include moving within and between cages, opening and closing gates, and mounting and riding animals. The Traffic World includes vehicles moving continuously between road crossings subject to a number of restrictions, such as speed limits and keeping a fixed safety distance away from other vehicles on the road. We show how to represent the two domains in the input language of CCALC, and how to use CCALC to test these representations.
14238943
Secure query processing against encrypted XML data using Query-Aware Decryption
Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of Query-Aware Decryption for efficient processing of queries against encrypted XML data. Query-Aware Decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to six times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.
207320410
On fast supervised learning for normal mixture models with missing information
It is an important research issue to deal with mixture models when missing values occur in the data. In this paper, computational strategies using auxiliary indicator matrices are introduced for efficiently handling mixtures of multivariate normal distributions when the data are missing at random and have an arbitrary missing data pattern, meaning that missing data can occur anywhere. We develop a novel EM algorithm that can dramatically save computation time and be exploited in many applications, such as density estimation, supervised clustering and prediction of missing values. In the aspect of multiple imputations for missing data, we also offer a data augmentation scheme using the Gibbs sampler. Our proposed methodologies are illustrated through some real data sets with varying proportions of missing values.
42871030
An Efficient Method for Detection of Key Objects in Video Shots with Camera Motions
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