Recognition of hand-written archive text documents
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
A mixed reality head-mounted text translation system using eye gaze input
Proceedings of the 19th international conference on Intelligent User Interfaces
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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.