Beyond audio and video retrieval: topic-oriented multimedia summarization
نویسندگان
چکیده
منابع مشابه
Video retrieval and summarization
This year, it is anticipated that 25% of the population of the wealthy countries will have a digital television camera at their disposal. The combined capacity to generate bits from these devices is astronomical. In addition, the growth in computer speed, disc capacity, and, most of all, the rapid growth of the Internet and WWWwill make this information accessible worldwide. The immediate quest...
متن کاملVideo Retrieval und Video Summarization
Zusammenfassung Diese Arbeit behandelt die Problematik des Video Retrieval, das heiÿt der inhaltsbasierten Suche nach Videos in Multimedia Datenbanken, und in diesem Zusammenhang auch die Video Summarization, der Zusammenfassung von Videos. Es werden alle Schritte betrachtet, die nötig sind, um Video Retrieval durchführen zu können. Anfangs wird die Analyse der Videodaten betrachtet, die statt ...
متن کاملIntroduction Video retrieval and summarization
This year, it is anticipated that 25% of the population of the wealthy countries will have a digital television camera at their disposal. The combined capacity to generate bits from these devices is astronomical. In addition, the growth in computer speed, disc capacity, and, most of all, the rapid growth of the Internet and WWW will make this information accessible worldwide. The immediate ques...
متن کاملTime Oriented Video Summarization
This paper addresses a novel video summarization procedure that produces a dynamic (video) abstract of the original video sequence. To remain temporal characteristic in the video abstract, a newly time-oriented feature is introduced. The approach relies on time instances, frame rate of the original video sequence and display speed of the video summary to select frames for a video abstract. This...
متن کاملLatent Topic Modeling for Audio Corpus Summarization
This work presents techniques for automatically summarizing the topical content of an audio corpus. Probabilistic latent semantic analysis (PLSA) is used to learn a set of latent topics in an unsupervised fashion. These latent topics are ranked by their relative importance in the corpus and a summary of each topic is generated from signature words that aptly describe the content of that topic. ...
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ژورنال
عنوان ژورنال: International Journal of Multimedia Information Retrieval
سال: 2013
ISSN: 2192-6611,2192-662X
DOI: 10.1007/s13735-012-0028-y