On-Site Assisted Photography
On-Site Assisted Photography

Research suggests photos are the preferred choice of transit riders for documenting problems in public transit. However, for people who are blind or low vision, taking a good picture can be problematic.

Methods for automatic image cropping, image adaptation for small displays, image or video retargeting are possible approaches for improving pictures. Nonetheless, these methods are designed for image post–processing, and tend to rely in composition heuristics that may not apply to photographers with visual impairments. For example, on-center compositions, where a dominant subject is geometrically centered in the image, are taken for granted in consumer photography and unlikely for users who are blind.

Project Description

In this project, we propose a computational approach for assisting users with visual impairments during photographic documentation of transit problems. The problem of taking a “good” picture is difficult, but dramatically simplified by the task characteristics. First, aesthetics are not an issue for problem documentation, thereby mitigating a significant challenge. Second, we do not need to know what the barrier is – we only need to know where it is. While being able to automatically annotate barriers might be useful for documentation, it is not essential. This mitigates the need for object recognition. Third, we can assume the rider is able to localize the barrier in space and roughly aim a camera at the target.

Our key insight is to integrate user interaction during the image capturing process, such that users can take better pictures in real time. Our approach can be described as a method to avoid leaving out information that is expected to be the most relevant. Motivated by Gestalt theories, we evaluate a meaningful group of contiguous salient points in a picture as potential region of interest (ROI). The system tries to center this region in a photo and correct excessive camera roll.


This work was funded by grant number H133E080019 from the United States Department of Education through the National Institute on Disability and Rehabilitation Research.

M. Vázquez, A. Steinfeld. An Assisted Photography Framework to Help Visually Impaired Users Properly Aim a Camera. ACM Transactions on Computer-Human Interaction, v. 21, n. 5, p. 25:1-25:29, 2014.

M. Vázquez, A. Steinfeld. Helping Visually Impaired Users Properly Aim a Camera. Proc. of the 14th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), 2012.

M. Vázquez, A. Steinfeld. Facilitating Photographic Documentation of Accessibility in Street Scenes. Proc. of the Extended Abstracts on Human Factors in Computing Systems (CHI EA), 2011.

M. Vázquez, A. Steinfeld. An Assisted Photography Method for Street Scenes. Proc. of the 2011 IEEE Workshop on Applications of Computer Vision (WACV), 2011.