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D.R.O.P.S. : drop-off recognition optical processing system

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Title: D.R.O.P.S. : drop-off recognition optical processing system
Author: Saxena, Pranav; Yee, Rosanna
Issue Date: 2011-04-23
Publicly Available in cIRcle 2011-11-28
Series/Report no. University of British Columbia. Engineering Projects Project Lab. APSC 459, Project Conclusion Reports, 2011
Abstract: The purpose of this project is to design and develop a drop-off detection system to assist people with vision loss in navigating their surroundings. The system uses two cameras to successfully detect sudden drop-offs, such as stairs, curbs, edges of sky train platforms, etc. The system then provides aural feedback to appropriately notify the user of drop-offs. The research objectives involved learning how to analyze and process images from two cameras to detect drop-offs, using edge detection in conjunction with stereo vision to accurately and consistently locate drop-offs. From testing, it was found that the depth calculations were reasonably accurate with an error of 4.22 cm and meet our error margin of 7.62 cm (3 inches). However, the coefficient of variation was much higher than expected at 48.8%. The average processing speed was 6.21 frames per second which is one-fifth of the Minoru’s sampling speed. In our testing we found that the Minoru camera was not designed for outdoor use in very bright conditions, as the lighting can overwhelm the input and make it difficult to perform analysis. It was also required for street curbs to have an edge on the road, so that there is an edge to compare with the edge of the curb as seen in the image. There are various improvements that could be made to the current system. Currently, speech feedback is not implemented; instead, a series of beeps are used to warn the user. Outdoor performance could be improved by adding an optical filter to the Minoru camera. Calculations for the distance between the user and the drop-off are inaccurate, due to correlation errors from edge-noisy drop-offs. The fixture holding the Minoru could be redesigned to be more user-friendly. Optimization of the algorithms could also improve processing speeds. A working prototype has been demonstrated to the project sponsor Dr. Leung. This project has the potential to greatly benefit people that are visually impaired by providing a cost-effective, user-friendly, and useful tool to help them navigate their everyday environment.
Affiliation: Applied Science, Faculty ofEngineering Physics
URI: http://hdl.handle.net/2429/39323
Peer Review Status: Unreviewed
Scholarly Level: Undergraduate

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