Automatic image annotation by an iterative approach: incorporating keyword correlations and region matching

Automatic image annotation automatically labels image content with semantic keywords. For instance, the Relevance Model estimates the joint probability of the keyword and the image [3]. Most of the previous annotation methods assign keywords separately. Recently the correlation between annotated keywords has been used to improve image annotation. However, directly estimating the joint probability of a set of keywords and the unlabeled image is computationally prohibitive. To avoid the computation difficulty we propose a heuristic greedy iterative algorithm to estimate the probability of a keyword subset being the caption of an image. In our approach, the correlations between keywords are analyzed by “Automatic Local Analysis” of text information retrieval. In addition, a new image generation probability estimation method is proposed based on region matching. We demonstrate that our iterative annotation algorithm can incorporate the keyword correlations and the region matching appr...

• Type: Conference
• Year: 2007
• Where: CIVR
• Authors: Xiangdong Zhou, Mei Wang, Qi Zhang, Junqi Zhang, Baile Shi
• Keywords: Automatic Image Annotation, CIVR 2007, Image Annotation, Keywords