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Recognizing Words in Scenes with a Head-Mounted Eye-Tracker

机译:识别使用头戴式追踪器的场景中的单词

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Recognition of scene text using a hand-held camera is emerging as a hot topic of research. In this paper, we investigate the use of a head-mounted eye-tracker for scene text recognition. An eye-tracker detects the position of the user's gaze. Using gaze information of the user, we can provide the user with more information about his region/object of interest in a ubiquitous manner. Therefore, we can realize a service such as the user gazes at a certain word and soon obtain the related information of the word by combining a word recognition system with eye-tracking technology. Such a service is useful since the user has to do nothing but gazes at interested words. With a view to realize the service, we experimentally evaluate the effectiveness of using the eye-tracker for word recognition. The initial results show the recognition accuracy was around 70% in our word recognition experiment and the average computational time was less than one second per a query image.
机译:使用手持式相机识别现场文本作为研究的热门话题。 在本文中,我们调查了用于场景文本识别的头戴式追踪器的使用。 眼跟踪器检测用户凝视的位置。 使用用户的凝视信息,我们可以以无处不在的方式为用户提供有关他地区/兴趣对象的更多信息。 因此,我们可以通过组合具有眼跟踪技术的单词识别系统来实现诸如用户凝视的服务诸如用户凝视的服务。 这种服务很有用,因为用户只能在感兴趣的话语中凝视。 为了实现服务的视图,我们通过实验评估使用眼跟踪器进行Word识别的有效性。 初始结果表明,我们的单词识别实验中的识别精度约为70%,并且平均计算时间每次查询图像小于一秒钟。

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