Image Annotation in a Progressive Way

Automatic image annotation is crucial for keyword-based image retrieval because it can be used to improve the textual description of images efficiently. For this purpose, many methods have been developed. Due to the restrictions of computational complexity and small training set, the image annotation methods are usually based on the probability of individual word, instead of the joint probability of a set of words. Therefore the correlation between words is omitted. In this paper, we propose a method to approximate the joint probability of words in a progressive way. Given an image, the word with highest probability is first annotated. Then, the successive words are annotated by incorporating the information of previously annotated words. It can be seen as a "greedy" algorithm to calculate the joint probability of multiple words. The experiments show that the proposed progressive annotation method can effectively improve the annotation performance.