Building Detection and Recognition for an Automated Tour Guide

We present a building recognition module for an automated tour guide system which, instead of using user input or artificial landmarks, relies solely on real-time video recorded from a wearable camcorder to recognize faces of buildings and localize the user. Strong vertical edges are first detected on each frame to suggest the existence of building objects. Additional information such as color feature is collected to eliminate edges from trees, cars, and pedestrians. Vertical edges, in addition to horizontal edges, are further processed to locate window frames and thereafter faces of a building. An image section identified as a building face is then rectified for perspective distortion and recognized by a neural network. We train the neural network using whole and partial building face images before the recognition takes place.

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