Title :
Visual Summarization of the Social Image Collection Using Image Attractiveness Learned from Social Behaviors
Author :
Jin-Woo Jeong ; Hyun-Ki Hong ; Jee-Uk Heu ; Qasim, I. ; Dong-Ho Lee
Author_Institution :
Knowledge & Data Eng. Lab., Hanyang Univ., Seoul, South Korea
Abstract :
How to effectively summarize a large-scale image collection is still an important and open problem. In this paper, we propose a novel method to effectively generate a summary of the social image collection using image attractiveness learned from the social behaviors conducted in Flickr. To this end, we exploit the note information of Flickr images. The notes of Flickr images are user generated bounding boxes with text annotations assigned on the interesting image regions. Using the visual features extracted from the images that have notes, we have generated the attractiveness models for various concepts. Finally, the attractiveness models are exploited to make a summary of the social image collection. Through various user studies on the image collections from Flickr groups, we show the feasibility of our method and discuss further directions.
Keywords :
behavioural sciences; feature extraction; image processing; social networking (online); Flickr groups; Flickr images; attractiveness models; image attractiveness; image regions; large-scale image collection; social behaviors; social image collection; user generated bounding boxes; visual feature extraction; visual summarization; Clustering algorithms; Feature extraction; Integrated circuit modeling; Search problems; Semantics; Vectors; Visualization; Flickr note; image attractiveness; image interestingness; image summary; search result clustering;
Conference_Titel :
Multimedia and Expo (ICME), 2012 IEEE International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-1659-0
DOI :
10.1109/ICME.2012.196