An algorithm for wipe detection
The detection of transitions between shots in video programs is an important first step in analyzing video content. The wipe is a frequently used transitional form between shots. Wipe detection is more involved than the detection of abrupt and other gradual transitions because a wipe may take various patterns and because of the difficulty in discriminating a wipe from object and camera motion. In this paper, we propose an algorithm for detecting wipes using both structural and statistical information. The algorithm can effectively detect most wipes used in current TV programs. It uses the DC sequence which can be easily extracted from the MPEG stream without full decompression.

title: Forensic analysis of nonlinear collusion attacks for multimedia fingerprinting
abstract: Digital fingerprinting is a technology for tracing the distribution of multimedia content and protecting them from unauthorized redistribution. Unique identification information is embedded into each distributed copy of multimedia signal and serves as a digital fingerprint. Collusion attack is a cost-effective attack against digital fingerprinting, where colluders combine several copies with the same content but different fingerprints to remove or attenuate the original fingerprints. In this paper, we investigate the average collusion attack and several basic nonlinear collusions on independent Gaussian fingerprints, and study their effectiveness and the impact on the perceptual quality. With unbounded Gaussian fingerprints, perceivable distortion may exist in the fingerprinted copies as well as the copies after the collusion attacks. In order to remove this perceptual distortion, we introduce bounded Gaussian-like fingerprints and study their performance under collusion attacks. We also study several commonly used detection statistics and analyze their performance under collusion attacks. We further propose a preprocessing technique of the extracted fingerprints specifically for collusion scenarios to improve the detection performance.

title: Classification-based spatial error concealment for images
abstract: This paper presents a new, classification-based spatial error concealment algorithm for images. The proposed scheme takes advantage of two state-of-the-art concealment schemes and adaptively selects a better suitable concealment scheme for each corrupted block. Using a support vector machine (SVM) classifier, our proposed approach outperforms the prior art in terms of the concealment quality and has moderate computational complexity.

title: Data hiding in curves for collusion-resistant digital fingerprinting
abstract: This paper presents a new data hiding method for curves. The proposed algorithm parameterizes a curve using the B-spline model and adds a spread spectrum sequence in the coordinates of the B-spline control points. We demonstrate through experiments the robustness of the proposed data hiding algorithm against printing-and-scanning and collusions, and show its feasibility for collusion-resistant fingerprinting of topographic maps as well as writings/drawings from pen-based input devices.

title: Fingerprinting Curves
abstract: This paper presents a new method for robust data hiding in curves and highlights potential applications including digital fingerprinting of map document for trace and track purposes. We parameterize a curve using the B-spline model and add a spread spectrum sequence to the coordinates of the B-spline control points. In order to achieve robust fingerprint detection, we propose an iterative alignment-minimization algorithm to perform curve registration and deal with the non-uniqueness of B-spline control points. We show through experiments the robustness of our method against various attacks such as collusion, geometric transformations and perturbation, printing-and-scanning, and some of their combinations. We demonstrate the feasibility of our method for fingerprinting topographic maps as well as writings and drawings. The extension from hiding data in 2D topographic maps to 3D elevation data sets is also discussed.

title: Security evaluation for communication-friendly encryption of multimedia
abstract: This paper addresses the access control issues unique to multimedia, by using a joint signal processing and cryptographic approach to multimedia encryption. Based on three atomic encryption primitives, we present a systematic study on how to strategically integrate different atomic operations to build a video encryption system. We also propose a set of multimedia-specific security metrics to quantify the security against approximation attacks and to complement the existing notion of generic data security. The resulting system can provide superior performance to both generic encryption and its simple adaptation to video in terms of a joint consideration of security, bitrate overhead, and communication friendliness.

title: EITH - A Unifying Representation for Database Schema and Application Code in Enterprise Knowledge Extraction
abstract: The integration of heterogeneous legacy databases requires understanding of database structure and content. We previously developed a theoretical and software infrastructure to support the extraction of schema and business rule information from legacy sources, combining database reverse engineering with semantic analysis of associated application code (DRE/SA). In this paper, we present a compact formalism called EITH that unifies the representation of database schema and application code. EITH can be efficiently derived from various types of schema representations, particularly the relational model, and supports comparison of a wide variety of schema and code constructs to enable interoperation. Unlike UML or E/R diagrams, for example, EITH has compact notation, is unambiguous, and uses a small set of efficient heuristics. We show how EITH is employed in the context of SEEK, using a construction project management example. We also show how EITH can represent various structures in relational databases, and can serve as an efficient representation for E/R diagrams. This suggests that EITH can support efficient matching of more complex, hierarchical structures via indexed tree representations, without compromising the EITH design philosophy or formalism.

title: Informing the Design of Direct-Touch Tabletops
abstract: Tables provide a large and natural interface for supporting direct manipulation of visual content for human-to-human interactions. Such surfaces also support collaboration, coordination, and parallel problem solving. However, the direct-touch table metaphor also presents considerable challenges, including the need for input methods that transcend traditional mouse- and keyboard-based designs. In this paper, we've designed, implemented, and studied a variety of tabletop user interfaces, interaction techniques, and usage scenarios

title: A Subspace Kernel for Nonlinear Feature Extraction
abstract: Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used preprocessing step in pattern classification and data mining tasks. Given a positive definite kernel function, it is well known that the input data are implicitly mapped to a feature space with usually very high dimensionality. The goal of KFE is to find a low dimensional subspace of this feature space, which retains most of the information needed for classification or data analysis. In this paper, we propose a subspace kernel based on which the feature extraction problem is transformed to a kernel parameter learning problem. The key observation is that when projecting data into a low dimensional subspace of the feature space, the parameters that are used for describing this subspace can be regarded as the parameters of the kernel function between the projected data. Therefore current kernel parameter learning methods can be adapted to optimize this parameterized kernel function. Experimental results are provided to validate the effectiveness of the proposed approach.

title: Using Document Relationships for Better Answers
abstract: In most retrieval systems the answer to a query is a ranked list of documents. There is little information about the ranking and no support for exploring the relationships that may exist between the documents. In this paper we consider the use of clustering answers to better support users satisfying their information needs. We show how clustering reflects the nature of some information needs, and how the clustering can be used to find more relevant documents than would be the case using simple lists. This work contributes to our approach of building answers to information needs, rather than simply providing lists.

title: A Hyperrelational Approach to Integration and Manipulation of Data in Multidatabase Systems
abstract: The issue of interoperability among multiple autonomous databases has attracted a lot of attention from researchers in these years. The past research on this issue can be roughly divided into two main categories: the tightly-integrated approach that integrate databases by building an integrated schema and the loosely-integrated approach that achieves interoperability by using a multidatabase language. Most of the past efforts focused on the issues in the first approach. The problem with the first approach is, however, that it lacks a convenient representation of the integrated schema at the system level and a sound mathematical basis for data manipulation in a multidatabase system. In this paper, we propose to use hyperrelations as a powerful and succinct model for the global level representation of heterogeneous database schemas. A hyperrelation has the structure of a relation, but its contents are the schemas of the semantically equivalent local relations in the databases. With this representation, the metadata of the global database, local databases and the data of these databases are all representable by using the structure of a relation. The impact of such a representation is that all the elegant features of relational systems can be easily extended to multidatabase systems. A hyperrelational algebra is designed accordingly. This algebra is performed at the multidatabase systems (MDBS) level such that query transformation and optimization is supported on a sound mathematical basis. The major contributions of this paper include: (1) Local relations of various schemas (even though they retain information of the same semantics) can be systematically mapped to hyperrelations. As the structure of a hyperrelation is similar to that of a relation, data manipulation and management tasks (such as design of the global query language and the view mechanism) are greatly facilitated. (2) The hyperrelational algebra provides a sound basis for query transformation and optimization in a MDBS.