17,475 research outputs found

    Using Sensor Metadata Streams to Identify Topics of Local Events in the City

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    In this paper, we study the emerging Information Retrieval (IR) task of local event retrieval using sensor metadata streams. Sensor metadata streams include information such as the crowd density from video processing, audio classifications, and social media activity. We propose to use these metadata streams to identify the topics of local events within a city, where each event topic corresponds to a set of terms representing a type of events such as a concert or a protest. We develop a supervised approach that is capable of mapping sensor metadata observations to an event topic. In addition to using a variety of sensor metadata observations about the current status of the environment as learning features, our approach incorporates additional background features to model cyclic event patterns. Through experimentation with data collected from two locations in a major Spanish city, we show that our approach markedly outperforms an alternative baseline. We also show that modelling background information improves event topic identification

    An examination of automatic video retrieval technology on access to the contents of an historical video archive

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    Purpose – This paper aims to provide an initial understanding of the constraints that historical video collections pose to video retrieval technology and the potential that online access offers to both archive and users. Design/methodology/approach – A small and unique collection of videos on customs and folklore was used as a case study. Multiple methods were employed to investigate the effectiveness of technology and the modality of user access. Automatic keyframe extraction was tested on the visual content while the audio stream was used for automatic classification of speech and music clips. The user access (search vs browse) was assessed in a controlled user evaluation. A focus group and a survey provided insight on the actual use of the analogue archive. The results of these multiple studies were then compared and integrated (triangulation). Findings – The amateur material challenged automatic techniques for video and audio indexing, thus suggesting that the technology must be tested against the material before deciding on a digitisation strategy. Two user interaction modalities, browsing vs searching, were tested in a user evaluation. Results show users preferred searching, but browsing becomes essential when the search engine fails in matching query and indexed words. Browsing was also valued for serendipitous discovery; however the organisation of the archive was judged cryptic and therefore of limited use. This indicates that the categorisation of an online archive should be thought of in terms of users who might not understand the current classification. The focus group and the survey showed clearly the advantage of online access even when the quality of the video surrogate is poor. The evidence gathered suggests that the creation of a digital version of a video archive requires a rethinking of the collection in terms of the new medium: a new archive should be specially designed to exploit the potential that the digital medium offers. Similarly, users' needs have to be considered before designing the digital library interface, as needs are likely to be different from those imagined. Originality/value – This paper is the first attempt to understand the advantages offered and limitations held by video retrieval technology for small video archives like those often found in special collections

    Blip10000: a social video dataset containing SPUG content for tagging and retrieval

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    The increasing amount of digital multimedia content available is inspiring potential new types of user interaction with video data. Users want to easilyfind the content by searching and browsing. For this reason, techniques are needed that allow automatic categorisation, searching the content and linking to related information. In this work, we present a dataset that contains comprehensive semi-professional user generated (SPUG) content, including audiovisual content, user-contributed metadata, automatic speech recognition transcripts, automatic shot boundary les, and social information for multiple `social levels'. We describe the principal characteristics of this dataset and present results that have been achieved on different tasks

    Indexing, browsing and searching of digital video

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    Video is a communications medium that normally brings together moving pictures with a synchronised audio track into a discrete piece or pieces of information. The size of a “piece ” of video can variously be referred to as a frame, a shot, a scene, a clip, a programme or an episode, and these are distinguished by their lengths and by their composition. We shall return to the definition of each of these in section 4 this chapter. In modern society, video is ver

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Video summarisation: A conceptual framework and survey of the state of the art

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    This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2007 Elsevier Inc.Video summaries provide condensed and succinct representations of the content of a video stream through a combination of still images, video segments, graphical representations and textual descriptors. This paper presents a conceptual framework for video summarisation derived from the research literature and used as a means for surveying the research literature. The framework distinguishes between video summarisation techniques (the methods used to process content from a source video stream to achieve a summarisation of that stream) and video summaries (outputs of video summarisation techniques). Video summarisation techniques are considered within three broad categories: internal (analyse information sourced directly from the video stream), external (analyse information not sourced directly from the video stream) and hybrid (analyse a combination of internal and external information). Video summaries are considered as a function of the type of content they are derived from (object, event, perception or feature based) and the functionality offered to the user for their consumption (interactive or static, personalised or generic). It is argued that video summarisation would benefit from greater incorporation of external information, particularly user based information that is unobtrusively sourced, in order to overcome longstanding challenges such as the semantic gap and providing video summaries that have greater relevance to individual users
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