Research Article
GHio-Ca: An Android Application for Automatic Image Classification
@INPROCEEDINGS{10.1007/978-3-319-76111-4_25, author={Davide Polonio and Federico Tavella and Marco Zanella and Armir Bujari}, title={GHio-Ca: An Android Application for Automatic Image Classification}, proceedings={Smart Objects and Technologies for Social Good. Third International Conference, GOODTECHS 2017, Pisa, Italy, November 29-30, 2017, Proceedings}, proceedings_a={GOODTECHS}, year={2018}, month={3}, keywords={Online social networks Social media sensing Computer vision Android Image recognition}, doi={10.1007/978-3-319-76111-4_25} }- Davide Polonio
Federico Tavella
Marco Zanella
Armir Bujari
Year: 2018
GHio-Ca: An Android Application for Automatic Image Classification
GOODTECHS
Springer
DOI: 10.1007/978-3-319-76111-4_25
Abstract
Online social networks (OSN) have revolutionized many aspects of our daily lives and have become the predominant platform where content is consumed and produced. This trend coupled with recent advances in the field of Artificial Intelligence (AI) have paved the way to many interesting features, enriching user experience in these social platforms. Photo sharing and tagging is an important activity contributing to the social media data ecosystem. These data once labeled constitute a fruitful input for the system which is exploited to better the services of interest to the user. However, these labeling activity is imperfect and user subjective, hence prone to errors inherent to the process. In this paper, we present the design and the analysis of an Android app (namely GHio-Ca), an automatic photo tagging service relying on state-of-the-art image recognition APIs. The application is presented to the user as a camera app used to share pictures on social networks while relying on external services to automatically retrieve tags best representing the picture theme. Along with the system description we present a user evaluation involving 30 subjects.
