图像到信号,信号到亮点

Sai Siddartha Maram, Neeraj Kumar, J. Rodrigues, S. Tanwar, Arjav Jain
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引用次数: 0

摘要

在本文中,我们提出了一个框架,从广播板球比赛中生成板球集锦。由于比赛的持续时间和规则,制作板球集锦是一个难题。我们将突出显示生成问题表述为键事件初始化和键事件闭包识别问题。我们提出了一个逆层次框架,它是通用的,能够自动生成广播板球比赛的集锦。我们引入了一种新的上下文感知的事件初始化方法和一种基于结构相似性索引的事件关闭检测方法。尽管亮点的质量是一个主观的衡量标准,但我们通过将其与各种指标的官方亮点进行比较来对我们的框架进行评估。我们还对生成的高光进行用户调查。用户的认可以及生成的亮点和官方亮点之间的重叠表明了我们框架的健壮性。
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Images to Signals, Signals to Highlights
In this paper, we propose a framework to generate cricket highlights from broadcasted cricket matches. Generating cricket highlights is a difficult problem, due to the duration and rules of the game. We formulate the highlight generation problem as a key-event initialization and key-event-closure identification problem. We propose an Inverse Hierarchical Framework, which is generic and capable of automatically generating highlights of a broadcasted cricket match. We introduce a novel context-aware approach for event-initialization and a Structural Similarity Index-based approach for event-closure detection. Despite the quality of highlights being a subjective measure we provide an evaluation of our framework by comparing it with official highlights on various metrics. We also perform a user-survey on the generated highlights. The approval of the users and overlap between the generated highlights and official highlights indicate the robustness of our framework.
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