Abstract
With almost 8 million blind and visually impaired persons in India, there is an urgent need for autonomous navigation systems to help them. Since most homes have stairs, it is crucial that they be automatically detected in real time. The division of stairs into "up" and "down" categories is the main topic of this essay. 3D point cloud photos taken with an Intel RealSense camera are used in the study. The Hough Transform is applied to the corresponding RGB image in order to extract a 1D feature along the stairs' length from the depth image. The Intel RealSense camera was used to build a balanced dataset of 170 point cloud images that represented both "up" and "down" stairs. Experimental results demonstrate that the proposed method achieves classification performances of 60% with SVM and 85% with MLP, showcasing the potential of the approach for realworld applications.
Published Version
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