Extraction of Significant Video Summaries by Dendrogram Analysis

In the current video analysis scenario, effective clustering of shots facilitates the access to the content and helps in understanding the associated semantics. This paper introduces a cluster analysis on shots which employs dendrogram representation to produce hierarchical summaries of the video document. Vector quantization codebooks are used to represent the visual content and to group the shots with similar chromatic consistency. The evaluation of the cluster codebook distortions, and the exploitation of the dependency relationships on the dendrograms, allow to obtain only a few significant summaries of the whole video. Finally the user can navigate through summaries and decide which one best suites his/her needs for eventual post-processing. The effectiveness of the proposed method is demonstrated by testing it on a collection of video-data from different kinds of programmes. Results are evaluated in terms of metrics that measure the content representational value of the summarization technique

Video Shot Clustering and Summarization through dendrograms

In the context of analysis of video documents, effective clustering of shots facilitates the access to the content and helps in understanding the associated semantics. This paper introduces a cluster analysis on video shots which employs dendrogram representation to produce hierarchical summaries of the video document. Vector quantization codebooks are used to represent the visual content and to group the shots with similar chromatic consistency. The evaluation of the cluster codebook distortions, and the exploitation of the dependency relationships on the dendrogram, allow to obtain only a few significant summaries of the whole video. Finally the user can navigate through summaries and decide which one best suites his/her needs for eventual post processing. The effectiveness of the proposed method is demonstrated, on a collection of different video programmes, in term of metrics that measure the content representational value of the summarization technique

Hierarchical Video Summaries by Dendrogram Cluster Analysis

In the current video analysis scenario, effective summarization of video sequences through shot clustering facilitates the access to the content and helps in understanding the associated semantics. This paper introduces a generic scheme to produce hierarchical summaries of the video document starting from a dendrogram representation of clusters of shots. The evaluation of the cluster distortions, and the exploitation of the dependency relationships between clusters on the dendrograms, allow to obtain only a few semantically significant summaries of the whole video. Finally the user can navigate through summaries and decide which one best suites his/her needs for eventual post-processing. The effectiveness of the proposed method is demonstrated by testing it on a collection of video-data from different kinds of programmes, using and comparing different visual features on color information. Results are evaluated in terms of metrics that measure the content representational value of the summarization technique

Hierarchical Structuring of Video Previews by Leading-Cluster-Analysis

3noClustering of shots is frequently used for accessing video data and enabling quick grasping of the associated content. In this work we first group video shots by a classic hierarchical algorithm, where shot content is described by a codebook of visual words and different codebooks are compared by a suitable measure of distortion. To deal with the high number of levels in a hierarchical tree, a novel procedure of Leading-Cluster-Analysis is then proposed to extract a reduced set of hierarchically arranged previews. The depth of the obtained structure is driven both from the nature of the visual content information, and by the user needs, who can navigate the obtained video previews at various levels of representation. The effectiveness of the proposed method is demonstrated by extensive tests and comparisons carried out on a large collection of video data. of digital videos has not been accompanied by a parallel increase in its accessibility. In this context, video abstraction techniques may represent a key components of a practical video management system: indeed a condensed video may be effective for a quick browsing or retrieval tasks. A commonly accepted type of abstract for generic videos does not exist yet, and the solutions investigated so far depend usually on the nature and the genre of video data.openopenBenini, Sergio; Migliorati, Pierangelo; Leonardi, RiccardoBenini, Sergio; Migliorati, Pierangelo; Leonardi, Riccard

Rushes summarization by IRIM consortium: redundancy removal and multi-feature fusion

International audienceIn this paper, we present the first participation of a consortium of French laboratories, IRIM, to the TRECVID 2008 BBC Rushes Summarization task. Our approach resorts to video skimming. We propose two methods to reduce redundancy, as rushes include several takes of scenes. We also take into account low and midlevel semantic features in an ad-hoc fusion method in order to retain only significant content

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

Procedure for searching of data or a group of data in a database

The present invention deals with a method to search one item or a group of similar items within a number of items stored in a database, where each item is assigned with a representative graphical information, such as an image, sound, or text which identifies and characterizes the item itself. The method includes the following steps: a) organizing the database as a relational structure where all the representative information are grouped in a number of subsets according to a predetermined criterion of similarity, so that the information contained in each subset show differences in the informative content below a predetermined threshold value; b) associating to at least one of the subsets a probability value which depends on the subset content and/or from the results of previous search procedures and/or from the status of the ongoing search; c) randomly selecting one among the subsets according to the probability value assigned at the previous step, and simultaneously reproducing at least one part of the information contained in the same subset; d) if the searched item is not within the reproduced ones, repeating at least the previous step, until the user is able to find some interesting information

Retrieval of video scenes by structural descriptors

Structural information, on the form of shot patterns and timing, plays an important role in scripted video, being consistently used by filmmakers as a way to convey meaning and significance into their work. For this reason, a video retrieval system can benefit from exploiting this kind of information. In this paper we propose a novel method for the retrieval of video scenes according to their structural similarity, based on graph-theoretical measures and vector quantization techniques. We show the results of our method in some scene retrieval experiments on a data set of 802 movie scenes, extracted from a set of 180 mainstream movies

Explainable pattern modelling and summarization in sensor equipped smart homes of elderly

In the next several decades, the proportion of the elderly population is expected to increase significantly. This has led to various efforts to help live them independently for longer periods of time. Smart homes equipped with sensors provide a potential solution by capturing various behavioral and physiological patterns of the residents. In this work, we develop techniques to model and detect changes in these patterns. The focus is on methods that are explainable in nature and allow for generating natural language descriptions. We propose a comprehensive change description framework that can detect unusual changes in the sensor parameters and describe the data leading to those changes in natural language. An approach that models and detects variations in physiological and behavioral routines of the elderly forms one part of the change description framework. The second part comes from a natural language generation system in which we identify important health-relevant features from the sensor parameters. Throughout this dissertation, we validate the developed techniques using both synthetic and real data obtained from the homes of the elderly living in sensor-equipped facilities. Using multiple real data retrospective case studies, we show that our methods are able to detect variations in the sensor data that are correlated with important health events in the elderly as recorded in their Electronic Health Records.Includes bibliographical reference

Automatic Summarization of Video Game Reviews

Τα ηλεκτρονικά παιχνίδια αποτελούν εδώ και πολλά χρόνια ένα μοναδικό μέσο αλληλεπίδρασης μεταξύ παιχτών και εταιρειών. Οι δυναμικές που εμφανίζονται μέσω των διαδικτυακών δημοσιεύσεων έχουν αυξήσει σημαντικά τον αριθμό των σχολίων ανά παιχνίδι, οδηγώντας στην ανάπτυξη ενδιαφερουσών κοινοτήτων. Αυτή η αύξηση έχει, με τη σειρά της, οδηγήσει στη δύσκολη αντιμετώπιση του τεράστιου όγκου και ποικίλης ποιότητας σχολίων σαν πηγή πληροφορίας. Αυτή η δουλειά εξετάζει αν και πως οι κριτικές ηλ. παιχνιδιών μπορούν να συνοψιστούν, βάση των προυπάρχουσων εννοιών στην περίληψη βασισμένη σε χαρακτηριστικά και στην ανάλυση συναισθήματος. Παρέχουμε αρχικά ένα τυπικό ορισμό του προβλήματος με σκοπό να θέσουμε τη βάση για την προσέγγιση που προτείνουμε. Έπειτα, αναπτύσσουμε μία βασική υλοποίηση, που προσπαθεί να αντιμετωπίσει τις μεμονωμένες υποεργασίες που συντελούν το πρόβλημα της περιλήψης κριτικών ηλ. παιχνιδιών. Πιο συγκεκριμένα, δεδομένου ενός συνόλου από κριτικές για ένα παιχνίδι, εφαρμόζουμε συσταδοποίηση κ-μέσων για να αναγνωρίσουμε ομάδες όμοιων προτάσεων. Στη συνέχεια χρησιμοποιούμε λίστες λέξεων με σκοπό να αντιστοιχίσουμε τις παραγόμενες συστάδες σε προκαθορισμένα χαρακτηρικά των ηλ. παιχνιδιών, όπως τα γραφικά και το gameplay. Εν συνεχεία, εφαρμόζουμε ανάλυση συναισθήματος χρησιμοποιώντας μία μέθοδο βασισμένη σε κανόνες με σκοπό να εξάγουμε τα συναισθήματα που κυριαρχούν στη συστάδα. Επιπροσθέτως, προσφέρουμε προκαταρκτικά ευρήματα για το κατά πόσο τα χαρακτηριστικά που εντοπίστηκαν σε ένα σύνολο από σχόλια μπορούν να αξιολογηθούν με συνέπεια από ανθρώπους. Αυτή η διαδικασία αξιολόγησης επιβεβαιώνει ότι οι υποεργασίες της περίληψης κριτικών είναι εφικτές και ορίζει μία μέθοδο για την αξιολόγηση της επίδοσης μελλοντικών συστημάτων.Video game reviews have constituted a unique means of interaction between players and companies for many years. The dynamics appearing through online publishing have significantly grown the number of comments per game, giving rise to very interesting communities. The growth has, in turn, led to a difficulty in dealing with the volume and varying quality of the comments as a source of information. This work studies whether and how game reviews can be summarized, based on the notions pre-existing in aspect-based summarization and sentiment analysis. We initially provide a formal definition of the problem in order to set the basis for our suggested approach. We then devise a baseline implementation, that attempts to tackle the individual subtasks that constitute the problem of video game review summarization. More precisely, given a set of reviews of a video game, we apply k-means clustering in order to identify groups of similar sentences. We then utilize word lists with the aim of mapping the produced clusters to predefined game aspects, like graphics and gameplay. Subsequently, we apply sentiment analysis using a rule-based method in order to extract the sentiments that pervade each cluster. Additionally, we offer preliminary findings on whether aspects detected in a set of comments can be consistently evaluated by human users. The evaluation ascertains that review summarization subtasks are achievable and sets a method for the evaluation of performance of future systems