论文标题
显示或不显示：从电子显示器视频中编辑敏感文本
To show or not to show: Redacting sensitive text from videos of electronic displays
论文作者
论文摘要
随着视频录制的越来越多的流行率，对可以维持记录人员隐私的工具的需求越来越大。在本文中，我们定义了一种使用光学特征识别（OCR）和自然语言处理（NLP）技术的组合从视频中编辑个人身份文本的方法。当与不同的OCR模型，特别是Tesseract和Google Cloud Vision（GCV）的OCR系统一起使用时，我们检查了这种方法的相对性能。对于拟议的方法，GCV的性能以准确性和速度显着高于Tesseract。最后，我们探讨了现实世界应用中这两种模型的优势和缺点。
With the increasing prevalence of video recordings there is a growing need for tools that can maintain the privacy of those recorded. In this paper, we define an approach for redacting personally identifiable text from videos using a combination of optical character recognition (OCR) and natural language processing (NLP) techniques. We examine the relative performance of this approach when used with different OCR models, specifically Tesseract and the OCR system from Google Cloud Vision (GCV). For the proposed approach the performance of GCV, in both accuracy and speed, is significantly higher than Tesseract. Finally, we explore the advantages and disadvantages of both models in real-world applications.
