5 research outputs found

    Activity-driven content adaptation for effective video summarisation

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    In this paper, we present a novel method for content adaptation and video summarization fully implemented in compressed-domain. Firstly, summarization of generic videos is modeled as the process of extracted human objects under various activities/events. Accordingly, frames are classified into five categories via fuzzy decision including shot changes (cut and gradual transitions), motion activities (camera motion and object motion) and others by using two inter-frame measurements. Secondly, human objects are detected using Haar-like features. With the detected human objects and attained frame categories, activity levels for each frame are determined to adapt with video contents. Continuous frames belonging to same category are grouped to form one activity entry as content of interest (COI) which will convert the original video into a series of activities. An overall adjustable quota is used to control the size of generated summarization for efficient streaming purpose. Upon this quota, the frames selected for summarization are determined by evenly sampling the accumulated activity levels for content adaptation. Quantitative evaluations have proved the effectiveness and efficiency of our proposed approach, which provides a more flexible and general solution for this topic as domain-specific tasks such as accurate recognition of objects can be avoided

    Hierarchical modelling and adaptive clustering for real-time summarization of rush videos

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    In this paper, we provide detailed descriptions of a proposed new algorithm for video summarization, which are also included in our submission to TRECVID'08 on BBC rush summarization. Firstly, rush videos are hierarchically modeled using the formal language technique. Secondly, shot detections are applied to introduce a new concept of V-unit for structuring videos in line with the hierarchical model, and thus junk frames within the model are effectively removed. Thirdly, adaptive clustering is employed to group shots into clusters to determine retakes for redundancy removal. Finally, each most representative shot selected from every cluster is ranked according to its length and sum of activity level for summarization. Competitive results have been achieved to prove the effectiveness and efficiency of our techniques, which are fully implemented in the compressed domain. Our work does not require high-level semantics such as object detection and speech/audio analysis which provides a more flexible and general solution for this topic

    The romantic baby boomer: A successful aging analysis of romantic comedy film trailers

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    On any given Friday night, theaters across the United States are filled with teenagers and young adults, often to see the new Blockbuster that has just been released. The film industry has responded by producing content specifically targeted to this demographic. Unfortunately, this has left a major portion of the population waiting for material that is relatable. Even when there is a character over the age of 50, they are regularly for comic relief or portrayed as weak and incapable. The recent trend of romantic comedies incorporating storylines for older adults is still underrepresented in academic research. This thesis set out to understand the extent of successful aging content in romantic comedies with leading actresses and actors of the baby boomer generation. Content and textual analysis of 41 film trailers found a lack of individuality with many adhering to successful aging concepts and traditional gender roles. Additionally, age and associated effects including anxiety of death and the midlife transformation are supposed to be overcome, often with romance. Nevertheless, as directed in successful aging active engagement, sexual lives, high wealth and prime physical bodies was expected. However, the older characters are continuously compared to younger characters and both men and women desire the youthful bodies. This participatory research adds to the body of research on film trailers and aging in film, but is also applicable to the film industry as new films should include a variety of older characters in roles that embrace aging instead of pitying older adults
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