Geolocated Visual Summarization of Social Media Data Sosyal Medya Verilerinin Cografi Olarak Gorsel Ozeti
28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Türkiye, 5 - 07 Ekim 2020, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/siu49456.2020.9302210
- Basıldığı Şehir: Gaziantep
- Basıldığı Ülke: Türkiye
- Anahtar Kelimeler: feature extraction, Flickr, geo-tagged images, image processing, location information, SIFT, social media analysis
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
The usage of social media is increasing day by day. People use social media platforms to communicate with their friends or other users and to demonstrate what they are interested in by sharing different kinds of media such as photos, texts, and videos. A portion of the posted content also include location information. Such posts having location information are called geo-tagged posts in social networks. According to the analysis of geo-tagged posts, popular locations or activities can be identified. This study proposes a method to identify the most representative subset of the visual content shared in a region through social media. Our approach aims to detect the popular places and events and utilizes Scale-Invariant Feature Transform (SIFT) features. Identified representative visuals are used to generate a web based tourist map. In this study, Flickr is used as the source of geotagged visual content.