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UCap: A crowdsourcing application for the visually impaired and blind persons on Android smartphone

机译:UCap:针对Android智能手机上视障人士和盲人的众包应用程序

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One of the visual challenge problems that the blind faces is the consumer product identification with contextual and description information problem. In order to increase their independence in food shopping and other product recognition, we implement an Android application called UCap to assist the blind in this visual challenge problem. In the visually impaired and blind persons mode, UCap is a camera-base mobile application that identifies the consumer product of a captured image using the UCap annotated image database. The UCap annotated image database is created using the crowdsourcing paradigm. In the sighted user mode, the user can use UCap to capture an image of a consumer product, add its description, and upload them to the UCap annotated image database. The sighted user can add more images of the existing products in the database. The seed database contains 3,950 annotated images. We used Infrastructure-as-a-Service (IaaS) on MS Azure cloud server for the initial system testing and evaluation. With exception of the lower-than-expected accuracy of image identification, the application received high praised from the visually impaired and blind persons. However, from the experiment and testing, the accuracy of UCap can be increased as more images are added to the database.
机译:盲人面对的视觉挑战问题之一是带有上下文和描述信息问题的消费品标识。为了提高他们在食品购物和其他产品识别方面的独立性,我们实现了一个名为UCap的Android应用程序,以帮助盲人解决这一视觉挑战问题。在视障人士和盲人模式下,UCap是基于摄像头的移动应用程序,它使用UCap带注释的图像数据库来标识捕获图像的消费产品。 UCap带注释的图像数据库是使用众包范式创建的。在可见用户模式下,用户可以使用UCap捕获消费产品的图像,添加其描述,然后将其上载到带注释的UCap图像数据库。目标用户可以在数据库中添加现有产品的更多图像。种子数据库包含3,950个带批注的图像。我们在MS Azure云服务器上使用基础架构即服务(IaaS)进行了初始系统测试和评估。除了图像识别的精度低于预期之外,该应用程序还受到了视障人士和盲人的高度评价。但是,通过实验和测试,随着将更多图像添加到数据库中,可以提高UCap的准确性。

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