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Cognitive dynamic video summarization using cognitive analysis enriched feature set

机译:使用认知分析丰富特征集的认知动态视频摘要

摘要

Accurate and concise summarization of a media production is achieved using cognitive analysis which groups segments of the production into clusters based on extracted features, selects a representative segment for each cluster, and combines the representative segments to form a summary. The production is separated into a video stream, a speech stream and an audio stream, from which the cognitive analysis extracts visual features, textual features, and aural features. The clustering groups segments together whose visual and textual features most closely match. Selection of the representative segments derives a score for each segment based on factors including a distance to a centroid of the cluster, an emotion level, an audio uniqueness, and a video uniqueness. Each of these factors can be weighted, and the weights can be adjusted in accordance with user input. The factors can have initial weights which are based on statistical attributes of historical media productions.
机译:使用认知分析可以准确准确地总结媒体制作,该分析基于提取的特征将制作的各个部分分组为多个类,为每个类选择一个代表性部分,然后将这些代表性部分组合起来以形成摘要。作品分为视频流,语音流和音频流,认知分析从中提取视觉特征,文本特征和听觉特征。聚类分组将视觉和文字特征最紧密匹配的分段组合在一起。代表性片段的选择基于包括到群集的质心的距离,情感水平,音频唯一性和视频唯一性在内的因素得出每个片段的分数。可以对这些因素中的每一个进行加权,并且可以根据用户输入来调整权重。这些因素可以具有初始权重,该初始权重基于历史媒体作品的统计属性。

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