This paper proposes a real-world event detection method by using the time and location information and text tags attached to the images in Flickr. Events can generally be detected by extracting images captured at the events which are annotated with text tags frequently used only in specific times and locations. However, such approach can not detect events where only a small number of images were captured. We focus on the fact that semantically related events often occur around the same time at different locations. Considering a group of these events as an event class, the proposed method firstly detects event classes from all images in Flickr based on their similarity of the captured time and text tags. Then, from the images consisting each event class, events are detected based on their similarity of the captured locations. Such two-step approach enables us to detect events where a small number of images were captured.
['Naoko Nitta', 'Yusuke Kumihashi', 'Tomochika Kato', 'Noboru Babaguchi']
Real-World Event Detection Using Flickr Images