Stairway Detection Based on Single Camera by Motion Stereo for the Blind and Visually Impaired

This chapter presents a method to solve the stairway localization and recognition problem for both indoor and outdoor cases by using a convolutional neural network technique. To blind and visually impaired persons, these assistive technology application has an important impact on their daily life. The algorithm should be able to solve the problem of stair classification for both cases, indoor and outdoor scenes. The proposed idea describes the strategy for introducing an affordable method that can recognize stairways without taking into account the environments. First, this method uses stair features to classify images by using convolutional neural networks. Second, stairway candidate is extracted by using the Gabor filter a linear filter. Third, the set of lines that belong to the ground plane are removed by using the behavioral distance measurement between two consecutive frames. Finally, from this step, we extract the tread depth and the riser height of the stairways.