Data hiding in curves for collusion-resistant digital fingerprinting
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: 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: 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: Watermarking for image authentication
abstract: A data embedding method is proposed for image authentication based on table look-up in frequency domain. A visually meaningful watermark and a set of simple features are embedded invisibly in the marked image, which can be stored in the compressed form. The scheme can detect and localize alterations of the original image, such as the tampering of images exported from a digital camera.

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 binary image for authentication and annotation
abstract: This paper proposes a new method to embed data in binary images, including scanned text, figures, and signatures. The method manipulates "flippable" pixels to enforce specific block-based relationship in order to embed a significant amount of data without causing noticeable artifacts. Shuffling is applied before embedding to equalize the uneven embedding capacity from region to region. The hidden data can be extracted without using the original image, and can also be accurately extracted after high quality printing and scanning with the help of a few registration marks. The proposed data embedding method can be used to detect unauthorized use of a digitized signature, and annotate or authenticate binary documents. The paper also presents analysis and discussions on robustness and security issues.

title: Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays
abstract: Recent advances in sensing technology have enabled a new generation of tabletop displays that can sense multiple points of input from several users simultaneously. However, apart from a few demonstration techniques [17], current user interfaces do not take advantage of this increased input bandwidth. We present a variety of multifinger and whole hand gestural interaction techniques for these displays that leverage and extend the types of actions that people perform when interacting on real physical tabletops. Apart from gestural input techniques, we also explore interaction and visualization techniques for supporting shared spaces, awareness, and privacy. These techniques are demonstrated within a prototype room furniture layout application, called RoomPlanner.

title: Building Sparse Large Margin Classifiers
abstract: This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The added constraint explicitly controls the sparseness of the classifier and an approach is provided to solve the formulated problem. When considering the dual of this problem. it can be seen that building an SLMC is equivalent to constructing an SVM with a modified kernel function. Further analysis of this kernel function indicates that the proposed approach essentially finds a discriminating subspace that can be spanned by a small number of vectors, and in this subspace different classes of data are linearly well separated. Experimental results over several classification benchmarks show that in most cases the proposed approach outperforms the state-of-art sparse learning algorithms.

title: Encoded bitmap indexing for data warehouses
abstract: Complex query types, huge data volumes, and very high read/update ratios make the indexing techniques designed and tuned for traditional database systems unsuitable for data warehouses (DW). We propose an encoded bitmap indexing for DWs which improves the performance of known bitmap indexing in the case of large cardinality domains. A performance analysis and theorems which identify properties of good encodings for better performance are presented. We compare encoded bitmap indexing with related techniques, such as bit slicing, projection-, dynamic-, and range-based indexing.

title: Outlier detection by sampling with accuracy guarantees
abstract: An effective approach to detecting anomalous points in a data setis distance-based outlier detection. This paper describes a simplesampling algorithm to effciently detect distance-based outliers indomains where each and every distance computation is veryexpensive. Unlike any existing algorithms, the sampling algorithmrequires a xed number of distance computations and can return goodresults with accuracy guarantees. The most computationallyexpensive aspect of estimating the accuracy of the result issorting all of the distances computed by the sampling algorithm.The experimental study on two expensive domains as well as tenadditional real-life datasets demonstrates both the effciency andeffectiveness of the sampling algorithm in comparison with thestate-of-the-art algorithm and there liability of the accuracyguarantees.

title: The role of a judge in a user based retrieval experiment (poster session)
abstract: A tuning device for tympani that displays the pitch of each instrument's tympanum. The pitch is determined by measuring the strain in an adjustable tensioning mechanism employed in all tympani to keep proper tension on the tympanum. The pitch or tone of the tympani is determined by the vibration frequency of the tympanum when the tympani is played and the frequency is determined by the tension in the tympanum. A transducer measures the strain in the tensioning mechanism to give an accurate indication of what the tympanum tension, and therefore the pitch, of the tympani would be when played. The transducer includes a resistance-type strain gage mounted on the tympanum tensioning mechanism. The length of the conductor in the strain gage and therefore its resistance, changes with stress changes in the tensioning mechanism used to tune the tympani. A switch means selects a desired one of the strain gages mounted on each of the one or more tympani for inclusion as one section of a four-section resistance bridge circuit configuration. A signal conditioning module provides excitation to the bridge circuit and also conditions the output of the bridge circuit. The output of the bridge circuit varies as the resistance of the strain gage varies. The conditioned output of the bridge circuit is displayed on a voltmeter whose scale has been calibrated to indicate the pitch of the tympani being monitored.