title: Anti-Blur Feedback for Visually Impaired Users of Smartphone Cameras.
abstract: 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.
authors.affiliation: The Smith-Kettlewell Eye Research Institute 2318 Fillmore St. San Francisco, CA 94115 USA.
authors.forename: Pannag R
authors.initials: PR
authors.lastname: Sanketi
authors.affiliation: The Smith-Kettlewell Eye Research Institute 2318 Fillmore St. San Francisco, CA 94115 USA.
authors.forename: James M
authors.initials: JM
authors.lastname: Coughlan
keywords: Algorithms; Experimentation; Human Factors; Performance