Personal guidance system for the visually impaired
Assets '94 Proceedings of the first annual ACM conference on Assistive technologies
Activity and Location Recognition Using Wearable Sensors
IEEE Pervasive Computing
The steerable pyramid: a flexible architecture for multi-scale derivative computation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Recognizing User Context via Wearable Sensors
ISWC '00 Proceedings of the 4th IEEE International Symposium on Wearable Computers
Context-based vision system for place and object recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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Recognizing a user's location is the most challenging problem for providing intelligent location-based services. In this paper, we presented a realtime camera-based system for the place recognition problem. This system takes streams of scene images of a learned environment from user-worn cameras and produces the class label of the current place as an output. Multiple cameras are used to collect multi-directional scene images because utilizing multiple images yields better and robust recognition than a single image. For more robust recognition, we utilized spatial relationships between the places. In addition that, a temporal reasoning is incorporated with a Markov model to reflect typical staying time at each place. Recognition experiments, which were conducted in a real environment in a university campus, showed that the proposed method yields a very promising result.