Sanketi Pannag R, Coughlan James M
The Smith-Kettlewell Eye Research Institute 2318 Fillmore St. San Francisco, CA 94115 USA.
ASSETS. 2010 Oct;2010:233-234. doi: 10.1145/1878803.1878847.
A wide range of smartphone applications are emerging that employ image processing and computer vision algorithms to interpret the contents of images acquired by the phone's built-in camera, including applications that read product barcodes and recognize a variety of documents and other objects. However, almost all of these applications are designed for normally sighted users; a major barrier for visually impaired users (who might benefit greatly from such applications) is the difficulty of taking good-quality images. To overcome this barrier, this paper focuses on reducing the incidence of motion blur, caused by camera shake and other movements, which is a common cause of poor-quality, unusable images. We propose a simple technique for detecting camera shake, using the smartphone's built-in accelerometer (i.e. tilt sensor) to alert the user in real-time to any shake, providing feedback that enables him/her to hold the camera more steadily. A preliminary experiment with a blind iPhone user demonstrates the feasibility of the approach.
各种各样的智能手机应用程序正在涌现,它们采用图像处理和计算机视觉算法来解读通过手机内置摄像头获取的图像内容,包括读取产品条形码以及识别各种文档和其他物体的应用程序。然而,几乎所有这些应用程序都是为视力正常的用户设计的;对于视障用户(他们可能会从这类应用程序中受益匪浅)来说,一个主要障碍是难以拍摄出高质量的图像。为了克服这一障碍,本文着重于减少由相机抖动和其他移动引起的运动模糊的发生率,运动模糊是导致图像质量差、无法使用的常见原因。我们提出了一种简单的技术来检测相机抖动,利用智能手机的内置加速度计(即倾斜传感器)实时提醒用户任何抖动情况,提供反馈以便用户能更稳定地握持相机。对一位失明的iPhone用户进行的初步实验证明了该方法的可行性。