405 research outputs found
Key Phrase Extraction of Lightly Filtered Broadcast News
This paper explores the impact of light filtering on automatic key phrase
extraction (AKE) applied to Broadcast News (BN). Key phrases are words and
expressions that best characterize the content of a document. Key phrases are
often used to index the document or as features in further processing. This
makes improvements in AKE accuracy particularly important. We hypothesized that
filtering out marginally relevant sentences from a document would improve AKE
accuracy. Our experiments confirmed this hypothesis. Elimination of as little
as 10% of the document sentences lead to a 2% improvement in AKE precision and
recall. AKE is built over MAUI toolkit that follows a supervised learning
approach. We trained and tested our AKE method on a gold standard made of 8 BN
programs containing 110 manually annotated news stories. The experiments were
conducted within a Multimedia Monitoring Solution (MMS) system for TV and radio
news/programs, running daily, and monitoring 12 TV and 4 radio channels.Comment: In 15th International Conference on Text, Speech and Dialogue (TSD
2012
Automated generation of movie tributes
O objetivo desta tese é gerar um tributo a um filme sob a forma de videoclip, considerando como entrada um filme e um segmento musical coerente. Um tributo é considerado um vídeo que contém os clips mais significativos de um filme, reproduzidos
sequencialmente, enquanto uma música toca. Nesta proposta, os clips a constar do tributo final são o resultado da sumarização das legendas do filme com um algoritmo de sumarização genérico. É importante que o artefacto seja coerente e fluido, pelo que há a
necessidade de haver um equilíbrio entre a seleção de conteúdo importante e a seleção de conteúdo que esteja em harmonia com a música. Para tal, os clips são filtrados de forma a garantir que apenas aqueles que contêm a mesma emoção da música aparecem
no vídeo final. Tal é feito através da extração de vetores de características áudio relacionadas com emoções das cenas às quais os clips pertencem e da música, e, de seguida, da sua comparação por meio do cálculo de uma medida de distância. Por fim, os clips
filtrados preenchem a música cronologicamente. Os resultados foram positivos: em média, os tributos produzidos obtiveram 7 pontos, numa escala de 0 a 10, em critérios como seleção de conteúdo e coerência emocional, fruto de avaliação humana.This thesis’ purpose is to generate a movie tribute in the form of a videoclip for a given movie and music. A tribute is considered to be a video containing meaningful clips from the movie playing along with a cohesive music piece. In this work, we collect the clips by summarizing the movie subtitles with a generic summarization algorithm. It is important that the artifact is coherent and fluid, hence there is the need to balance between the selection of important content and the selection of content that is in harmony with the music. To achieve so, clips are filtered so as to ensure that only those that
contain the same emotion as the music are chosen to appear in the final video. This is made by extracting vectors of emotion-related audio features from the scenes they belong to and from the music, and then comparing them with a distance measure. Finally, filtered clips fill the music length in a chronological order. Results were positive: on average, the produced tributes obtained scores of 7, on a scale from 0 to 10, on content selection, and emotional coherence criteria, from human evaluation
Summarization of Films and Documentaries Based on Subtitles and Scripts
We assess the performance of generic text summarization algorithms applied to
films and documentaries, using the well-known behavior of summarization of news
articles as reference. We use three datasets: (i) news articles, (ii) film
scripts and subtitles, and (iii) documentary subtitles. Standard ROUGE metrics
are used for comparing generated summaries against news abstracts, plot
summaries, and synopses. We show that the best performing algorithms are LSA,
for news articles and documentaries, and LexRank and Support Sets, for films.
Despite the different nature of films and documentaries, their relative
behavior is in accordance with that obtained for news articles.Comment: 7 pages, 9 tables, 4 figures, submitted to Pattern Recognition
Letters (Elsevier
Summarization from Medical Documents: A Survey
Objective:
The aim of this paper is to survey the recent work in medical documents
summarization.
Background:
During the last decade, documents summarization got increasing attention by
the AI research community. More recently it also attracted the interest of the
medical research community as well, due to the enormous growth of information
that is available to the physicians and researchers in medicine, through the
large and growing number of published journals, conference proceedings, medical
sites and portals on the World Wide Web, electronic medical records, etc.
Methodology:
This survey gives first a general background on documents summarization,
presenting the factors that summarization depends upon, discussing evaluation
issues and describing briefly the various types of summarization techniques. It
then examines the characteristics of the medical domain through the different
types of medical documents. Finally, it presents and discusses the
summarization techniques used so far in the medical domain, referring to the
corresponding systems and their characteristics.
Discussion and conclusions:
The paper discusses thoroughly the promising paths for future research in
medical documents summarization. It mainly focuses on the issue of scaling to
large collections of documents in various languages and from different media,
on personalization issues, on portability to new sub-domains, and on the
integration of summarization technology in practical applicationsComment: 21 pages, 4 table
A comprehensive survey of multi-view video summarization
[EN] There has been an exponential growth in the amount of visual data on a daily basis acquired from single or multi-view surveillance camera networks. This massive amount of data requires efficient mechanisms such as video summarization to ensure that only significant data are reported and the redundancy is reduced. Multi-view video summarization (MVS) is a less redundant and more concise way of providing information from the video content of all the cameras in the form of either keyframes or video segments. This paper presents an overview of the existing strategies proposed for MVS, including their advantages and drawbacks. Our survey covers the genericsteps in MVS, such as the pre-processing of video data, feature extraction, and post-processing followed by summary generation. We also describe the datasets that are available for the evaluation of MVS. Finally, we examine the major current issues related to MVS and put forward the recommendations for future research(1). (C) 2020 Elsevier Ltd. All rights reserved.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A2B5B01070067)Hussain, T.; Muhammad, K.; Ding, W.; Lloret, J.; Baik, SW.; De Albuquerque, VHC. (2021). A comprehensive survey of multi-view video summarization. Pattern Recognition. 109:1-15. https://doi.org/10.1016/j.patcog.2020.10756711510
Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy
In this paper we shall consider the problem of deploying attention to subsets
of the video streams for collating the most relevant data and information of
interest related to a given task. We formalize this monitoring problem as a
foraging problem. We propose a probabilistic framework to model observer's
attentive behavior as the behavior of a forager. The forager, moment to moment,
focuses its attention on the most informative stream/camera, detects
interesting objects or activities, or switches to a more profitable stream. The
approach proposed here is suitable to be exploited for multi-stream video
summarization. Meanwhile, it can serve as a preliminary step for more
sophisticated video surveillance, e.g. activity and behavior analysis.
Experimental results achieved on the UCR Videoweb Activities Dataset, a
publicly available dataset, are presented to illustrate the utility of the
proposed technique.Comment: Accepted to IEEE Transactions on Image Processin
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