Footballs Video Scene Retrieval with Interactive Genetic Algorithm

Qing-kai Bu, A. Hu
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引用次数: 1

Abstract

This paper proposed an interactive genetic algorithm (IGA) for football video scenes retrieval with multimodal features. Four audio-visual features (average shot duration, average motion activity average sound energy, and average speech rate) were extracted from each of the videos. Then they were encoded as chromosomes and indexed into search table. First, the proposed algorithm randomly selected the videos from the initial population of videos database, and the user selected what he (she) wanted in mind. Next, the associated chromosomes of selected videos were regarded as target chromosomes after crossover and chromosomes in the database videos were compared based on similarity function to obtain the most similar videos as solutions of the next generation. By iterating this process, a new population of videos was retrieved. This approach of retrieval shows about 84% of effectiveness on the average over 200 videos.
基于交互式遗传算法的足球视频场景检索
提出了一种基于多模态特征的交互式遗传算法(IGA)。从每个视频中提取四种视听特征(平均镜头时长、平均运动活动、平均声能和平均语音率)。然后将它们编码为染色体并编入检索表。首先,该算法从视频数据库的初始填充中随机选择视频,由用户选择自己想要的视频。然后,将所选视频的相关染色体作为交叉后的目标染色体,并基于相似度函数对数据库视频中的染色体进行比较,得到最相似的视频作为下一代的解。通过迭代这一过程,检索到新的视频种群。这种检索方法在200多个视频中平均显示出84%的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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