Consistent structure determination of a noisy measurement system model

This paper describes a fast and accurate method for defining the structure of a noisy measurement system model without a previous parameters evaluation. The procedure is based on the following steps: (i) choosing a stable system structure; (ii) determing the real model order; (iii) estimating the model parameters. In (i) a value of the model order greater than the supposed one is assumed; in (ii), in order to determine the real structure, samples of the input/output signals of the actual model and the over-parametrised one are used; in (iii), by means of unbiased identification techniques, the model parameters are evaluated. The proposed method can be used both in batch and real-time processing. Experimental results concerning a single input-single output linear process with different model order and noise statistical properties are given.     

Recommending multimedia visiting paths in cultural heritage applications

The valorization and promotion of worldwide Cultural Heritage by the adoption of Information and Communication Technologies represent nowadays some of the most important research issues with a large variety of potential applications. This challenge is particularly perceived in the Italian scenario, where the artistic patrimony is one of the most diverse and rich of the world, able to attract millions of visitors every year to monuments, archaeological sites and museums. In this paper, we present a general recommendation framework able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context-aware recommendation techniques supporting intelligent multimedia services for the users—i.e. dynamic visiting paths for a given environment. Specific applications of our system within the cultural heritage domain are proposed by means of real case studies in the mobile environment related both to an outdoor and indoor scenario, together with some results on user’s satisfaction and system accuracy.     

A study of co-occurrence based local features for camera model identification

Camera model identification has great relevance for many forensic applications, and is receiving growing attention in the literature. Virtually all techniques rely on the traces left in the image by the long sequence of in-camera processes which are specific of each model. They differ in the prior assumptions, if any, and in how such evidence is gathered in expressive features. In this work we study a class of blind features, based on the analysis of the image residuals of all color bands. They are extracted locally, based on co-occurrence matrices of selected neighbors, and then used to train a classifier. A number of experiments are carried out on the well-known Dresden Image Database. Besides the full-knowledge case, where all models of interest are known in advance, other scenarios with more limited knowledge and partially corrupted images are also investigated. Experimental results show these features to provide a state-of-the-art performance.     

Segmentation of news videos based on audio-video information

In this paper, we propose an innovative architecture to segment a news video into the so-called “stories” by both using the included video and audio information. Segmentation of news into stories is one of the key issues for achieving efficient treatment of news-based digital libraries. While the relevance of this research problem is widely recognized in the scientific community, we are in presence of a few established solutions in the field. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a novel anchor shot detection method based on features extracted from the audio track. Tests on a large database confirm that the proposed system outperforms each single video-based method as well as their combination.

A Formal Model for Video Shot Segmentation and its Application via Animate Vision

The first step in a video indexing process is the segmentation of videos into meaningful parts called shots. In this paper we present a formal model of the video shot segmentation process. Starting from a mathematical characterization of the most common transition effects, a video segmentation algorithm capable to detect both abrupt and gradual transitions is proposed. The proposed algorithm is based on the computation of an arbitrary similarity measure between consecutive frames of a video. The algorithm has been tested adopting a similarity metric based on the Animate Vision theory and results have been reported.     

Combining experts for anchorperson shot detection in news videos

Automatic classification of shots extracted by news videos plays an important role in the context of news video segmentation, which is an essential step towards effective indexing of broadcasters digital databases. In spite of the efforts reported by the researchers involved in this field, no techniques providing fully satisfactory performance have been presented until now. In this paper, we propose a multi-expert approach for unsupervised shot classification. The proposed multi-expert system (MES) combines three algorithms that are model-free and do not require a specific training phase. In order to assess the performance of the MES, we built up a database significantly wider than those typically used in the field. Experimental results demonstrate the effectiveness of the proposed approach both in terms of shot classification and of news story detection capability.     

A comparison of fitting algorithms for diffusion-weighted MRI data analysis using an intravoxel incoherent motion model

Object

The objective of this study is to propose a modified VARiable PROjection (VARPRO) algorithm specifically tailored for fitting the intravoxel incoherent motion (IVIM) model to diffusion-weighted magnetic resonance imaging (DW-MRI) data from locally advanced rectal cancer (LARC).

Materials and methods

The proposed algorithm is compared with classical non-linear least squares (NLLS) analysis using the Levenberg-Marquardt (LM) algorithm and with two recently proposed algorithms for ‘segmented’ analysis. These latter two comprise two consecutive steps: first, a subset of parameters is estimated using a portion of data; second, the remaining parameters are estimated using the whole data and the previous estimates. The comparison between the algorithms was based on the \(R^2\) goodness-of-fit measure: performance analysis was carried out on real data obtained by DW-MRI on 40 LARC patients.

Results

The performance of the proposed algorithm was higher than that of LM in 64 % of cases; ‘segmented’ methods were poorer than our algorithm in 100 % of cases.

Conclusion

The proposed modified VARPRO algorithm can lead to better fit of the IVIM model to LARC DW-MRI data compared to other techniques.

     

Effects of High Pressure Treatments on Polymeric Films for Flexible Food Packaging

Effects of high pressure (HP) treatments on functional and morphological properties of commercial packaging films have been investigated, to assess their suitability for use in these processes. Experimental analyses have been performed on packaging films, used to make pouches containing four different types of food simulants, after HP pasteurization and sterilization treatments at 200, 500 and 700 MPa. The investigated polymeric flexible packaging structures were single layer as well as bilayer films. Effects of treatments on structural/morphological properties (i.e. crystallinity and density) and on thermodynamic and barrier properties were addressed. Quite all the investigated films were found to be suitable for HP pasteurization, which only determined a negligible effect on the glass transition temperatures and on density of the amorphous regions of some polymeric materials, without a significant effect on functional properties of the packaging. Only bilayer structures including metalized polyethyleneterephthalate were not able to withstand processing conditions because of an extensive delamination accompanied by loss of metallization layer. Conversely, in the case of HP sterilization, combined effects of HP and relatively high temperature caused significant modifications in some of the packaging materials, even those not including a metalized film. In particular, localized delamination occurred in the case of bilayer structures made by laminating polyethyleneterephtalate with linear low density polyethylene or with polypropylene. Films obtained by laminating cast polyamide and bioriented polyamide with polypropylene displayed no evidence of delamination. In the case of films not displaying delamination, only limited changes in gas and vapour barrier properties were detected. Copyright © 2014 John Wiley & Sons, Ltd.