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The Washington Research Foundation Fellowship
Josh Scotland, Computer Science and Business Administration, 2011-11 WRFF
I embarked on my journey of accessibility research three years ago, right after getting into the Computer Science department. I was lucky to have met Dr. Richard Ladner and be chosen to take lead on one of his projects. Deciding to do research was one of the best and most rewarding choices I have made.
Since then, I have been involved with several projects, studies, workshops, and outreach programs where I have gained insight into how the accessibility industry works and what needs to be improved. Upon completion of my first project, I was able to increase the usability of tactile images and successfully integrate an audio component into the automated workflow.
My passion lies in making the world a better place by pushing the limits of software. I want to thank the Washington Research Foundation for this wonderful opportunity to have a big impact on the world of computational photography for greater accessibility. I am confident my research will yield results that will help people of any kind feel less restricted by insufficient visual information.
Mentor: Richard Ladner, Computer Science & Engineering
Project Title: Computational Photography for Greater Accessibility
Abstract: Images are a powerful way to communicate, preserve, and educate. Their powerful expressiveness has led to much research over the past several decades to improve photography. The latest development is computational photography, which is an emerging field of study that uses sensory information to compute the final photo. The goal is to improve images by combining digital data with computing power to generate superior images. Techniques that represent computational photography include panoramic stitching, high-dynamic-range (HDR) imaging, and light-field imaging.
Andrew Adams, a leading Stanford researcher behind computational photography, released a fully programmable digital camera system to aid other researchers in computational photography. Named FCam, it is an open-source C++ application programmable interface (API) for easy and precise control of digital cameras. My research will focus on using the FCam API to develop faster, smarter algorithms to create images for accessibility purposes.
Computational photography can be directly applied to several accessibility research projects. Initially, I will only focus on two. The first application is for VizWiz, which is a talking mobile phone application that answers visual questions in nearly real time. The second application of my computational photography research is for MobileOCR. After taking a photo of printed text, MobileOCR reads the text aloud using an intuitive screen reader. VizWiz and MobileOCR are just two of the many accessibility applications that can benefit from computational photography.