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Gaze location prediction for broadcast football video using Bayesian integration of low level features and top-down cues

机译:使用低级功能和自上而下的线索的贝叶斯集成,对广播的足球视频进行注视位置预测

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Accurate prediction of the viewer's gaze location has the potential to improve bit allocation, rate control, error resilience and quality evaluation in video compression. With complex contexts, such as that of broadcast football video, the potential reward is even higher given that compression and transmission of this type of content is challenging. In this paper we propose a gaze location prediction system for high definition broadcast football video. The proposed system employs Bayesian integration of bottom-up features and context specific top-down cues. Our results show that the proposed model has better gaze prediction performance than other top-down models that we adapted to this context.
机译:观众视线位置的准确预测可能会改善视频压缩中的比特分配,速率控制,错误恢复能力和质量评估。在复杂的环境中,例如广播足球视频,鉴于压缩和传输此类内容具有挑战性,因此潜在的回报甚至更高。在本文中,我们提出了一种用于高清广播足球视频的注视位置预测系统。所提出的系统采用了自下而上的特征和上下文特定的自上而下的线索的贝叶斯集成。我们的结果表明,提出的模型比我们适应这种情况的其他自上而下模型具有更好的凝视预测性能。

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