8968053
Resource-Bounded Balanced Genericity, Stochasticity and Weak Randomness
We introduce balanced t(n)-genericity which is a refinement of the genericity concept of Ambos-Spies, Fleischhack and Huwig [2] and which in addition controls the frequency with which a condition is met. We show that this concept coincides with the resource-bounded version of Church's stochasticity [6]. By uniformly describing these concepts and weaker notions of stochasticity introduced by Wilber [19] and Ko [11] in terms of prediction functions, we clarify the relations among these resource-bounded stochasticity concepts. Moreover, we give descriptions of these concepts in the framework of Lutz's resource-bounded measure theory [13] based on martingales: We show that t(n)-stochasticity coincides with a weak notion of t(n)-randomness based on so-called simple martingales but that it is strictly weaker than t(n)-randomness in the sense of Lutz.
5135938
Privacy preserving database application testing
Traditionally, application software developers carry out their tests on their own local development databases. However, such local databases usually have only a small number of sample data and hence cannot simulate satisfactorily a live environment, especially in terms of performance and scalability testing. On the other hand, the idea of testing applications over live production databases is increasingly problematic in most situations primarily due to the fact that such use of live production databases has the potential to expose sensitive data to an unauthorized tester and to incorrectly update information in the underlying database. In this paper, we investigate techniques to generate mock databases for application software testing without revealing any confidential information from the live production databases. Specifically, we will design mechanisms to create the deterministic rule set R, non-deterministic rule set N R, and statistic data set S for a live production database. We will then build a security Analyzer which will process the triplet <R',N R',S'> together with security requirements (security policy) and output a new triplet <R',N R',S'> The security Analyzer will guarantee that no confidential information could be inferred from the new triplet <R',N R',S'> The mock database generated from this new triplet can simulate the live environment for testing purpose, while maintaining the privacy of data in the original database.
6142906
Multiple attribute decision making based on fuzzy preference information on alternatives: Ranking and weighting
This paper investigates the multiple attribute decision making (MADM) problem with fuzzy preference information on alternatives and proposes an eigenvector method to rank them. Three optimization models are introduced to assess the relative importance weights of attributes in a MADM problem, which integrate subjective fuzzy preference relations and objective information in different ways. Since the decisions these models lead to are based on both subjective and objective information, they are more balanced and credible than those that consider only one type of information. An example is provided to illustrate the application of the proposed models.
46267544
Neighboring Feature Clustering
In spectral datasets, such as those consisting of MR spectral data derived from MS lesions, neighboring features tend to be highly correlated, suggesting the data lie on some low-dimensional space. Naturally, finding such low-dimensional space is of interest. Based on this real-life problem, this paper extracts an abstract problem, neighboring feature clustering (NFC). Noticeably different from traditional clustering schemes where the order of features doesn't matter, NFC requires that a cluster consist of neighboring features, that is features that are adjacent in the original feature ordering. NFC is then reduced to a piece-wise linear approximation problem. We use minimum description length (MDL) method to solve this reduced problem. The algorithm we proposed works well on synthetic datasets. NFC is an abstract problem. With minor changes, it can be applied to other fields where the problem of finding piece-wise neighboring groupings in a set of unlabeled data arises.
17258193
Spatiotemporal video segmentation based on graphical models
This paper proposes a probabilistic framework for spatiotemporal segmentation of video sequences. Motion information, boundary information from intensity segmentation, and spatial connectivity of segmentation are unified in the video segmentation process by means of graphical models. A Bayesian network is presented to model interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notion of the Markov random field is used to encourage the formation of continuous regions. Given consecutive frames, the conditional joint probability density of the three fields is maximized in an iterative way. To effectively utilize boundary information from the intensity segmentation, distance transformation is employed in local objective functions. Experimental results show that the method is robust and generates spatiotemporally coherent segmentation results. Moreover, the proposed video segmentation approach can be viewed as the compromise of previous motion based approaches and region merging approaches.
1211237
High Resolution Acquisition, Learning and Transfer of Dynamic 3D Facial Expressions
Synthesis and re-targeting of facial expressions is central to facial animation and often involves significant manual work in order to achieve realistic expressions, due to the difficulty of capturing high quality dynamic expression data. In this paper we address fundamental issues regarding the use of high quality dense 3-D data samples undergoing motions at video speeds, e.g. human facial expressions. In order to utilize such data for motion analysis and re-targeting, correspondences must be established between data in different frames of the same faces as well as between different faces. We present a data driven approach that consists of four parts: 1) High speed, high accuracy capture of moving faces without the use of markers, 2) Very precise tracking of facial motion using a multi-resolution deformable mesh, 3) A unified low dimensional mapping of dynamic facial motion that can separate expression style, and 4) Synthesis of novel expressions as a combination of expression styles. The accuracy and resolution of our method allows us to capture and track subtle expression details. The low dimensional representation of motion data in a unified embedding for all the subjects in the database allows for learning the most discriminating characteristics of each individual's expressions as that person's “expression style”. Thus new expressions can be synthesized, either as dynamic morphing between individuals, or as expression transfer from a source face to a target face, as demonstrated in a series of experiments. 
 
 
 
Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Animation; I.3.5 [Computer Graphics]: Curve, surface, solid, and object representations; I.3.3 [Computer Graphics]: Digitizing and scanning; I.2.10 [Artificial intelligence]: Motion ; I.2.10 [Artificial intelligence]: Representations, data structures, and transforms; I.2.10 [Artificial intelligence]: Shape; I.2.6 [Artificial intelligence]: Concept learning
206873031
Lossy compression of images using logic minimization
A technique for lossy compression of images is presented, utilizing ideas of logic minimization. The approach specifically addresses the compression of the binary image data originated in block truncation coding (BTC). The binary vector corresponding to a block of 4/spl times/4 pixels is treated as the output of a Boolean function and prime cubes are generated. The largest prime cube is encoded. Bit rate less than 1.5 bits/pel is attained in BTC without many perceivable errors in the reconstructed grey scale image. Training, pre-stored tables or codebooks, and prior knowledge of the image source are not required by the technique which uses simple logic operations. Computational simplicity of the algorithm makes it suitable for VLSI implementation. Potential of the technique in attaining a rate less than 0.5 bit/pel by applying it on image sequences and extending to blocks of larger size is indicated.