Robust error-resilient approach for MPEG video transmission over Internet
In network delivery of compressed video, packets may be lost if the channel is unreliable. Such losses tend to occur in burst. In this paper, we develop an error resilient video encoding approach to help error concealment at the decoder. We introduce a new block shuffling scheme to isolate erroneous blocks caused by packet losses. And we apply data hiding to add additional protection for motion vectors. The incorporation of these scheme adds little complexity to the standard encoder. Experimental results suggest that our approach can achieve a reasonable quality for packet loss up to 30% over a wide range of video materials.

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: Collusion-resistant multimedia fingerprinting: a unified framework
abstract: Digital fingerprints are unique labels inserted in different copies of the same content before distribution. Each digital fingerprint is assigned to an inteded recipient, and can be used to trace the culprits who use their content for unintended purposes. Attacks mounted by multiple users, known as collusion attacks, provide a cost-effective method for attenuating the identifying fingerprint from each coluder, thus collusion poses a reeal challenge to protect the digital media data and enforce usage policies. This paper examines a few major design methodologies for collusion-resistant fingerprinting of multimedia, and presents a unified framework that helps highlight the common issues and the uniqueness of different fingerprinting techniques.

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: Anti-collusion codes: multi-user and multimedia perspectives
abstract: Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content, such as images and video. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cheap and effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are averaged or combined to disrupt the underlying fingerprint. We present a construction of collusion-resistant fingerprints based upon anti-collusion codes (ACC) and binary code modulation. ACC have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we build fingerprints that allow for the identification of groups of K or less colluders. We present a construction of binary-valued ACC under the logical AND operation using the theory of combinatorial designs. Our code construction requires only /spl Oscr/(/spl radic/n) orthogonal signals to accommodate n users. We demonstrate the performance of our ACC for fingerprinting multimedia by identifying colluders through experiments using real images.

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: Participatory design of an orientation aid for amnesics
abstract: We present the participatory design and evaluation of an orientation aid for individuals who have anterograde amnesia. Our design team included six amnesics who have extreme difficulty storing new memories. We describe the methods we used to enable the participation of individuals with such severe cognitive impairments. Through this process, we have conceived, designed, and developed the OrientingTool, a software application for Personal Digital Assistants that can be used by amnesics to orient themselves when feeling lost or disoriented. Two complementary studies were conducted to evaluate the effectiveness of this tool in ecologically valid contexts. Our findings suggest that the OrientingTool can improve an amnesic's independence and confidence in managing situations when disoriented, and that participatory design may be productively used with participants who have significant cognitive disabilities.

title: Question-driven classification of retrieved documents
abstract: Many existing information access systems deliver ranked lists of documents in response to users' queries. Some systems also endeavour to represent some of the various types of relationships that can exist between documents. However, few systems provide effective mechanisms to help users discover useful information within the set of retrieved documents. In this paper, we present a question-driven approach to delivering retrieved documents in an attempt to organize them in a way that is closer to the user's mental representation of the expected answer. In our proposed approach, retrieved documents are dynamically classified into categories; an appropriate classification scheme is selected by a user on the basis of his own understanding of the information need. Experimental results show that users are more satisfied with such a directed categorization than with a list of retrieved documents.

title: Nonlinear V1 responses to natural scenes revealed by neural network analysis
abstract: A key goal in the study of visual processing is to obtain a comprehensive description of the relationship between visual stimuli and neuronal responses. One way to guide the search for models is to use a general nonparametric regression algorithm, such as a neural network. We have developed a multilayer feed-forward network algorithm that can be used to characterize nonlinear stimulus-response mapping functions of neurons in primary visual cortex (area V1) using natural image stimuli. The network is capable of extracting several known V1 response properties such as: orientation and spatial frequency tuning, the spatial phase invariance of complex cells, and direction selectivity. We present details of a method for training networks and visualizing their properties. We also compare how well conventional explicit models and those developed using neural networks can predict novel responses to natural scenes.

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: 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.