Claims about the emergence of a new type of social aggregation—“virtual community”—cover a type of ideological discourse about social interactions. The main cultural resource fueling this ideology is the counterculture and its social project. Virtual community, both as a discursive and as a social practice, is a culmination rather than a resolution of the modern conflict between community and individuality. Presenting virtual community as a panacea for modern social tensions, especially that between individualistic and communitarian ideals, hides from sight not only some of the negative aspects of on-line social life (cliquish behavior and incivility) but also the role played by communication technology in fragmenting modern society.

Wyner-Ziv video coding aims to design encoders based on the Slepian-Wolf and Wyner-Ziv distributed source coding theorems. In this coding scenario, source statistics are exploited at the decoder so that it is feasible to design simplified encoders. The shift of the computational complexity from the encoder to the decoder is suitable for emerging mobile multimedia applications. Many channel coding techniques are used for the construction of distributed video coding systems. In this paper we present a Wyner-Ziv video coding design using low-density parity-check (LDPC) codes. We also present a refined side estimator to further improve the decoded video quality. Experimental results are presented to demonstrate the rate-distortion performance of the method

Printer identification based on a printed document can provide forensic information to protect copyright and verify authenticity. In addition to intrinsic features (intrinsic signatures) of the printer, modulating the printing process to embed specific signatures (extrinsic signatures) will further extend the encoding capacity and utility. One of the key issues with embedding extrinsic signature is the embedded signature should not be detectable by the human observer but is detectable using a matched sensing device and detection algorithm. In this paper, we will investigate the modeling and experimental characterization of the EP process to obtain the modulation threshold such that the embedding signatures are below human visual threshold. An empirical model is established and a heuristic functional inverse is used to obtain the process modulation threshold.

In this paper we present two performance optimization methods for a motion compensated (MC) 2D wavelet video coding technique, which is based on two of the current state-of-the-art codecs: H.26L TML9.4 and JPEG2000 VM7.2. First, a new metric for motion vector selection is proposed to take both edge and texture complexity into account in motion prediction. Second, a frame level rate allocation algorithm, which is an extension of JPEG2000 PCRD (Post Compression Rate Distortion) optimization, is proposed. Experimental results demonstrate the significant performance improvements by these two techniques.

We propose a nested interleaving scheme in order to provide three levels of synchronization in a compressed video bitstream for low data rate wireless applications. The first level of interleaving specifies the starting position of each macroblock (MB) in a video frame. The second level of interleaving provides the start position of each MB header codeword and the start position of each DCT block. The start position of each VLC in a DCT block is located in a known position by the third level of interleaving. Our scheme is assumed to operate in the form of a transcoder, placed before and after the channel, of a MPEG-4 Simple Profile bitstream. Since the three level interleaving provides synchronization on a VLC scale, syntax-based bit error detections can be done in a VLC unit. The detected errors can be repaired syntactically so that the transcoder generates a MPEG-4 compliant bitstream which can then be decoded with a standard MPEG-4 decoder such as MoMuSys (FDIS V1.0).

We discuss in this paper the issues related to image watermarking benchmarking and scenarios based on digital rights management requirements. We show that improvements are needed in image quality evaluation, specially related to image geometrical deformation assessments, in risk evaluation related to specific delivery scenarios and in multidimensional criteria evaluation. Efficient benchmarking is still an open issue and we suggest the use of open-source Web-based evaluation systems for the collective progresses in this domain.

Studies of international telecommunication networks in past years have found increases in density, centralization, and integration. More recent studies, however, have identified trends of decentralization and regionalization. The present research examines these structural changes in international telephone traffic among 110 countries between 1989 and 1999. It examines the competing theoretical models of core-periphery and cluster structures. The initial results show lowered centralization and inequality in the network of international telecommunications traffic. Statistical p* procedures demonstrate significant interactions within countries in blocks of similar economic development status, geographic region, and telecommunications infrastructure development status. Specifically, countries with less developed economic and telecommunications status showed significant increases in tendencies to connect to each other and to reciprocate ties. Altogether, the result supports the idea that the global telecommunications network is moving toward a more diversified structure with the emergence of cohesive and interconnected subgroups. The findings have implications for global digital divide and developmental gap issues.

Digital watermarking of multimedia content has become a very active research area over the last several years. A general framework for watermark embedding and detection/decoding is presented here along with a review of some of the algorithms for different media types described in the literature. We highlight some of the differences based on application such as copyright protection, authentication, tamper detection, and data hiding as well as differences in technology and system requirements for different media types such as digital images, video, audio and text

This paper presents a novel audio and video information fusion approach that greatly improves automatic recognition of people in video sequences. To that end, audio and video information is first used independently to obtain confidence values that indicate the likelihood that a specific person appears in a video shot. Finally, a post-classifier is applied to fuse audio and visual confidence values. The system has been tested on several news sequences and the results indicate that a significant improvement in the recognition rate can be achieved when both modalities are used together.

We present new approaches based on Genetic Algorithms (GAs), Simulated Annealing (SA) and Expectation Maximization (EM) for determining parameters of the mixture Gaussian model. GAs are adaptive search techniques designed to search for near-optimal solutions of large-scale optimization problems with multiple local maxima. It has been shown that GAs are independent of initialization parameters and can efficiently optimize functions in large search spaces while the solution obtained by EM is a function of initial parameters. There is a relatively high likelihood of achieving sub-optimal solution, due to trapping in local maxima. In this work, we propose a combination of Genetic Algorithm with EM (Interlaced GA–EM) to improve estimation of Gaussian mixture parameters. The method uses population of mixture models, rather than a single mixture, iteratively in both GA and EM to determine Gaussian mixture parameters. To assess the performance of the proposed methods, a series of Gaussian phantoms, based on the ‘Modified Shepp–Logan’ method, were created. All proposed methods were employed to estimate the tissue parameters in each phantom and applied on Micro Computed Tomography (μCT) of dental images. The proposed method offers an accurate and stable solution for parameter estimation on Gaussian mixture models, with higher likelihood of achieving global optimal minima. Obtaining such accurate parameter estimation is a key requirement for image segmentation approach, which rely on a priori knowledge of tissue model parameters.

The coding efficiency of a Wyner-Ziv video codec relies significantly on the quality of side information extracted at the decoder. The construction of efficient side information is difficult thanks in part to the fact that the original video sequence is not available at the decoder. Conventional motion search methods are widely used in the Wyner-Ziv video decoder to extract the side information. This substantially increases the Wyner-Ziv video decoding complexity. In this paper, we propose a new method to construct side estimation based on the idea of universal prediction. This method, referred to as Wyner-Ziv video coding with universal prediction (WZUP), does not perform motion search or assume an underlying model of the original input video sequences at the decoder. Instead, WZUP estimates the side information based on its observations on the past reconstructed video data. We show that WZUP can significantly reduce decoding complexity at the decoder and achieve a fair side estimation performance, thus making it possible to design both the video encoder and the decoder with low computational complexity