Study On Tag Refinement And Tag Completion For Effective Image Retrieval
نویسندگان
چکیده
Online sharing of images is increasingly becoming popular, resulting in the availability of vast collections of user contributed images that have been annotated with user supplied tags. Many social image search engines are based on keyword/tag matching. It is because tag-based image retrieval (TBIR) is not only efficient but also effective. The performance of TBIR is highly dependent on the availability and quality of manual tags. Since many users tend to choose general and ambiguous tags in order to minimize their efforts in choosing appropriate tags, they are usually incomplete and insufficient to describe the whole semantic content of corresponding images resulting in unsatisfactory performances in tag related applications. This is a study on various techniques which are used to complete the missing tags and correct the noisy tags for given images thereby improving the retrieval performance.
منابع مشابه
Correlation consistency constrained probabilistic matrix factorization for social tag refinement
With the permeation of Web 2.0, large-scale user contributed images with tags are easily available on social websites. However, the noisy or incomplete correspondence between images and tags prohibit us from precise image retrieval and effective management. To tackle this, we propose a social tag refinement method, named as Correlation Consistency constrained Probabilistic Matrix Factorization ...
متن کاملImage tag refinement by regularized latent Dirichlet allocation
Tagging is nowadays the most prevalent and practical way to make images searchable. However, in reality many manually-assigned tags are irrelevant to image content and hence are not reliable for applications. A lot of recent efforts have been conducted to refine image tags. In this paper, we propose to do tag refinement from the angle of topic modeling and present a novel graphical model, regul...
متن کاملMICC-UNIFI at ImageCLEF 2013 Scalable Concept Image Annotation
In this paper we report on MICC participation to the Scalable Concept Image Annotation subtask of the ImageCLEF Photo Annotation and Retrieval competition [13]. Our goal has been to investigate the applicability of data-driven methods that have obtained good results in the field of social image annotation and retrieval to web images. These methods have been applied typically to tasks such as ta...
متن کاملImage tag completion via dual-view linear sparse reconstructions
User-provided textual tags of web images are widely utilized for facilitating image management and retrieval. Yet they are usually incomplete and insufficient to describe the whole semantic content of the corresponding images, resulting in performance degradations of various tag-dependent applications. In this paper, we propose a novel method denoted as DLSR for automatic image tag completion v...
متن کاملTags Re-ranking Using Multi-level Features in Automatic Image Annotation
Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image...
متن کامل