The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

We present an interactive, computational approach for assisting users with visual impairments during photographic documentation of transit problems. Our technique can be described as a method to improve picture composition, while retaining visual information that is expected to be most relevant. Our system considers the position of the estimated region of interest (ROI) of a photo, and camera orientation. Saliency maps and Gestalt theory are used for guiding the user towards a more balanced picture. Our current implementation for mobile phones uses optic flow to update the internal knowledge of the position of the ROI and tilt sensor readings to correct non horizontal or vertical camera orientations. Using ground truth labels, we confirmed our method proposes valid strategies for improving image composition. Future work includes an optimized implementation and user studies.

Notes

Sponsor: National Institute on Disability and Rehabilitation Research

Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Quality of Life Technology Center

Associated Lab(s) / Group(s): NavLab and Human-Robot Interaction Group

Associated Project(s): RERC on Accessible Public Transportation

Text Reference

Marynel Vazquez and Aaron Steinfeld, "An assisted photography method for street scenes," Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV) 2011, January, 2011.

BibTeX Reference

@inproceedings{Vazquez_2011_6775,
   author = "Marynel Vazquez and Aaron Steinfeld",
   title = "An assisted photography method for street scenes",
   booktitle = "Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV) 2011",
   month = "January",
   year = "2011",
}

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