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In this paper, we present a novel approach for visualizing large video collection on the web. Lei PangÂ and Wei Wang propose a framework that combines video analysis, clustering, and visualization techniques to create a galaxy-like representation of video collection. The framework can handle various types of videos, such as news, sports, entertainment, and education. The framework can also support different applications, such as video summarization, video browsing, video recommendation, video question-answering, and social video analysis. The main idea is to extract features from videos, cluster them based on their similarity and relevance, and map them to a two-dimensional space using a force-directed layout algorithm. The resulting visualization shows the videos as a galaxy of clusters, where each cluster corresponds to a topic or a theme. The user can interact with the visualization to explore the video collection in an intuitive and engaging way.
We evaluate our approach on a large video collection from YouTube, which contains over 100,000 videos from 16 categories. We compare our approach with several baseline methods, such as PCA, t-SNE, and UMAP. We use various metrics to measure the quality of the visualization, such as cluster purity, cluster separation, cluster coverage, and user satisfaction. The results show that our approach outperforms the baseline methods in terms of both quantitative and qualitative measures. Our approach can effectively capture the diversity and similarity of the video collection and provide a comprehensive and coherent overview of the video content.
We also conduct a user study to assess the usability and usefulness of our approach. We recruit 20 participants with different backgrounds and interests. We ask them to perform several tasks using our visualization system, such as finding videos related to a given topic, comparing videos from different categories, discovering new videos of interest, and answering questions based on the video content. We collect their feedback through questionnaires and interviews. The results show that most participants find our system easy to use, informative, and enjoyable. They also appreciate the galaxy metaphor and the interactive features of our system.
In conclusion, we propose a novel approach for visualizing large video collection on the web. Our approach combines video analysis, clustering, and visualization techniques to create a galaxy-like representation of video collection. Our approach can handle various types of videos and support different applications. Our approach can also provide an intuitive and engaging way for users to explore the video collection. We demonstrate the effectiveness and usefulness of our approach through experiments and user studies. We believe that our approach can open up new possibilities for video analysis and visualization on the web. 061ffe29dd