  Elevator button recognition is a critical function to realize the autonomous
operation of elevators. However, challenging image conditions and various image
distortions make it difficult to recognize buttons accurately. To fill this
gap, we propose a novel deep learning-based approach, which aims to
autonomously correct perspective distortions of elevator button images based on
button corner detection results. First, we leverage a novel image segmentation
model and the Hough Transform method to obtain button segmentation and button
corner detection results. Then, pixel coordinates of standard button corners
are used as reference features to estimate camera motions for correcting
perspective distortions. Fifteen elevator button images are captured from
different angles of view as the dataset. The experimental results demonstrate
that our proposed approach is capable of estimating camera motions and removing
perspective distortions of elevator button images with high accuracy.
