In recent years, we have assisted to an impressive advance of computer vision algorithms, based on image processing and artificial intelligence. Among the many applications of computer vision, in this paper we investigate on the potential impact for enhancing the cultural and physical accessibility of cultural heritage sites. By using a common smartphone as a mediation instrument with the environment, we demonstrate how convolutional networks can be trained for recognizing monuments in the surroundings of the users, thus enabling the possibility of accessing contents associated to the monument itself, or new forms of fruition for visually impaired people. Moreover, computer vision can also support autonomous mobility of people with visual disabilities, for identifying pre-defined paths in the cultural heritage sites, and reducing the distance between digital and real world.
|Title of host publication||IOP Conference Series: Materials Science and Engineering|
|Number of pages||8|
|Publication status||Published - 2020|
All Science Journal Classification (ASJC) codes
- General Materials Science
- General Engineering