Greg Olmschenk

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The World Health Organization estimates that 285 million people are visually impaired worldwide: 39 million are blind and 246 million have low vision. In order to improve the overall situation without having the user feel encumbered, our Crowd Assisted Navigation app is designed for smartphones (including both iPhones and Android phones), which are by far(More)
Real-time, low-resource corridor reconstruction using a single consumer grade RGB camera is a powerful tool for allowing a fast, inexpensive solution to indoor mobility of a visually impaired person or a robot. The perspective and known geometry of a corridor is used to extract the important features of the image and create a 3D model from a single image.(More)
We present a real-time algorithm that reconstructs 3D models of corridors using a mobile device. Contrary to previous approaches, our approach uses a noniterative, simultaneous model reconstruction method called J-Linkage, which is both accurate in parameter estimation and efficient in computation. We first use J-Linkage to find the vanishing points in a(More)
Crowdsourcing has been shown to be a powerful method for solving a variety of problems. In this paper, we introduce an approach for allowing a crowd to help navigate a visually impaired user to their destination in real-time. Furthermore, we experiment with several approaches in aggregating and feeding back crowd data to determine the optimal method. Our(More)
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