Abstract
Doors are significant landmarks for indoor wayfinding and navigation to assist blind people accessing unfamiliar environments. Most camera-based door detection algorithms are limited to familiar environments where doors demonstrate known and similar appearance features. In this paper, we present a robust image-based door detection algorithm based on doors’ general and stable features (edges and corners) instead of appearance features (color, texture, etc). A generic geometric door model is built to detect doors by combining edges and corners. Furthermore, additional geometric information is employed to distinguish doors from other objects with similar size and shape (e.g. bookshelf, cabinet, etc). The robustness and generalizability of the proposed detection algorithm are evaluated against a challenging database of doors collected from a variety of environments over a wide range of colors, textures, occlusions, illuminations, scale, and views.
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Tian, Y., Yang, X., Arditi, A. (2010). Computer Vision-Based Door Detection for Accessibility of Unfamiliar Environments to Blind Persons. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds) Computers Helping People with Special Needs. ICCHP 2010. Lecture Notes in Computer Science, vol 6180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14100-3_39
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DOI: https://doi.org/10.1007/978-3-642-14100-3_39
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