作者
Hongyun Cai, Yang Yang, Xuefei Li, Zi Huang
发表日期
2015/10/13
图书
Proceedings of the 23rd ACM international conference on Multimedia
页码范围
89-98
简介
As one of the most representative social media platforms, Twitter provides various real-life information on social events in real time. Despite that social event detection has been actively studied, tweet images, which appear in around 36 percent of the total tweets, have not been well utilized for this research problem. Most existing event detection methods tend to represent an image as a bag-of-visual-words and then process these visual words in the same way as textual words. This may not fully exploit the visual properties of images. State-of-the-art visual features like convolutional neural network (CNN) features have shown significant performance gains over the traditional bag-of-visual-words in unveiling the image's semantics. Unfortunately, they have not been employed in detecting events from social websites. Hence, how to make the most of tweet images to improve the performance of social event detection …
引用总数
201620172018201920202021202220232024651113139923
学术搜索中的文章
H Cai, Y Yang, X Li, Z Huang - Proceedings of the 23rd ACM international conference …, 2015