Estimating Dynamic Traffic Matrices by using Viable Routing Changes

Abstract: In this paper we propose a new approach for dealing with the ill-posed nature of traffic matrix estimation. We present three solution enhancers: an algorithm for deliberately changing link weights to obtain additional information that can make the underlying linear system full rank; a cyclo-stationary model to capture both long-term and short-term traffic variability, and a method for estimating the variance of origin-destination (OD) flows. We show how these three elements can be combined into a comprehensive traffic matrix estimation procedure that dramatically reduces the errors compared to existing methods. We demonstrate that our variance estimates can be used to identify the elephant OD flows, and we thus propose a variant of our algorithm that addresses the problem of estimating only the heavy flows in a traffic matrix. One of our key findings is that by focusing only on heavy flows, we can simplify the measurement and estimation procedure so as to render it more practical. Although there is a tradeoff between practicality and accuracy, we find that increasing the rank is so helpful that we can nevertheless keep the average errors consistently below the 10% carrier target error rate. We validate the effectiveness of our methodology and the intuition behind it using commercial traffic matrix data from Sprint's Tier-1 backbon

A New Phase Time Formula for Opaque Barrier Tunneling

After a brief review of the derivation of the standard phase time formula, based on the use of the stationary phase method, we propose, in the opaque limit, an alternative method to calculate the phase time. The new formula for the phase time is in excellent agreement with the numerical simulations and shows that for wave packets whose upper limit of the momentum distribution is very close to the barrier height, the transit time is proportional to the barrier width.Comment: 9 pages, 2 figure

Content and Description Scalability Issues in a Home Network Environment

In this document an integration of the preexisting requirements for Digital Item Adaptation is proposed. The new requirement comes out considering that in some cases to solely adapt resources such as MPEG-7 descriptions of a same multimedia document is not the best approach. In this circumstance in order provide the user with the best multimedia experience it would be better to allow mechanisms for the generation of a compact and rich descriptions obtained by the integration/simplification of the initials ones. The proposal is then to extend the DIA requirement stated in document N4684 in order to support the integration not only aggregation of multiple descriptions of the same content

Identification of editing effect in image sequences by statistical modeling

This paper presents a novel approach for video editing effect detection in digital image se- quences such as movies, commercials... The proposed method is based on histogram information and the decision criterion is derived from statistical properties of dissolve or wipe images, with respect to some hypothesis on the histograms of shots that surround the dissolve interval. More in particular the histogram of a dissolve image is given by the convolution of the histograms of two contiguous shots, provided that the random processes associated with the two shots are sta- tistically independent. A two step algorithm is presented: in the first step the dissolve effects are detected while in the second a precise estimate of the editing effect time interval is established. Simulation results indicate that high performance can be achieved with the proposed approach

Text Driven Recognition of Multiple Faces in Newspapers

Face recognition is still a hard task when performed on newspaper images, since they often show faces in non-frontal poses, prohibitive lighting conditions, and too poor quality in terms of resolution. In these cases, combining textual information derived from the page articles with visual information proves to be advantageous for improving the recognition performance. In this work, we extract characters’ names from articles and captions to restrict facial recognition to a limited set of candidates. To solve the difficulties derived from having multiple faces in the same image, we also propose a solution that enables a joint assignment of faces to characters’ names. Extensive tests in both ideal and real scenarios confirm the soundness of the proposed approach

Inferring semantics from structural annotations of audio–visual documents

In this paper, a new approach for semantic extraction is proposed. Assuming that the semantics of interest associated to a multimedia document is subjective and that the user cannot easily construct a semantic description on different abstraction levels, we propose an interactive tool which allows to generate a semantic description by organizing an audio-visual document. The structural decomposition is the result of a guided annotation by the user: the user segments the input sequence in events, assigns each event to a specific class and includes other informations such as time, place and contained objects. The classification process can evolve dynamically, which means that the user can organize the semantics with various personalized and more specialized classes. Using the resulting structural descriptions and classification, our method automatically generates a richer semantic description. The system is totally MPEG-7 complaint

Comparing the Quality of Multiple Descriptions of Multimedia Documents

With the definition of the MPEG-7 standard, thanks to its inter-operability behaviors, it is now possible for applications to use content descriptions of a same document, coming from different sources. This implies that the overall information available at the application can be highly redundant and mechanisms for filtering the information are hence required. In this work, a general approach to descriptions integration is proposed. The idea is to manipulate information readily available from the considered descriptions to reach an accurate integration result, without having to reprocess the multimedia material. The proposed general framework has been applied at a real problem showing how segment decompositions can be integrated on the basis of dominant color descriptors series. This work introduces also the concept of reliability of descriptor extraction methods demonstrating how it can be effectively used through the proposed integration process

An Overview of Video Shot Clustering and Summarization Techniques for Mobile Applications

The problem of content characterization of video programmes is of great interest because video appeals to large audiences and its efficient distribution over various networks should contribute to widespread usage of multimedia services. In this paper we analyze several techniques proposed in literature for content characterization of video programmes, including movies and sports, that could be helpful for mobile media consumption. In particular we focus our analysis on shot clustering methods and effective video summarization techniques since, in the current video analysis scenario, they facilitate the access to the content and help in quick understanding of the associated semantics. First we consider the shot clustering techniques based on low-level features, using visual, audio and motion information, even combined in a multi-modal fashion. Then we concentrate on summarization techniques, such as static storyboards, dynamic video skimming and the extraction of sport highlights. Discussed summarization methods can be employed in the development of tools that would be greatly useful to most mobile users: in fact these algorithms automatically shorten the original video while preserving most events by highlighting only the important content. The effectiveness of each approach has been analyzed, showing that it mainly depends on the kind of video programme it relates to, and the type of summary or highlights we are focusing on