The paper describes the problem of stopping the text field recognition process in a video stream, which is a novel problem, particularly relevant to real-time mobile document recognition systems. A decision-theoretic framework for this problem is provided, and similarities with existing stopping rule problems are explored. Following the theoretical works on monotone stopping rule problems, a strategy is proposed based on thresholding the estimation of the expected difference between consequent recognition results. The efficiency of this strategy is evaluated on an openly accessible dataset. The results show that this method outperforms the previously published methods based on identical results cluster size thresholding. Notes on future work include incorporation of recognition result confidence estimations in the proposed model and more precise evaluation of the observation cost.

中文翻译：

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基于单调顺序决策模型的视频流中文本识别的最佳停止策略

本文描述了在视频流中停止文本字段识别过程的问题，这是一个新颖的问题，尤其与实时移动文档识别系统有关。提供了针对该问题的决策理论框架，并探讨了与现有停止规则问题的相似性。根据有关单调停止规则问题的理论工作，提出了一种基于阈值估计结果之间的预期差异估计的策略。在可公开访问的数据集上评估此策略的效率。结果表明，基于相同的结果簇大小阈值，该方法优于以前发布的方法。