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A hybrid automatic image annotation approach
Multimedia Tools and Applications, 2018Automated image annotation (AIA) is an important issue in computer vision and pattern recognition, and plays an extremely important role in retrieving large-scale images. In many image annotation approaches, different regions of the image are processed equally, which is inconsistent with the mechanism by which humans understand images.
Cong Jin, Qing-Mei Sun, Shu-Wei Jin
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Automatic Image Annotation at ImageCLEF
2019Automatic image annotation is the task of automatically assigning some form of semantic label to images, such as words, phrases or sentences describing the objects, attributes, actions, and scenes depicted in the image. In this chapter, we present an overview of the various automatic image annotation tasks that were organized in conjunction with the ...
Wang, Josiah +3 more
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Automatic Emotion-Based Image Semantic Annotation
Applied Mechanics and Materials, 2013The image retrieval based on emotional keywords is required by users. But now it is short of ways to mark emotional semantic for images, especially the automatic methods, narrow and inaccurate. In this paper, we use the web images which are marked relatively comprehensively and accurately as training samples to generate emotional semantic.
Jing Jing Zhang, Yan Cao, Xiang Wei Mu
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Automatic image annotation with continuous PLSA
2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we firstly extend probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding Expectation-Maximization (EM) algorithm is derived to determine the model parameters.
Zhixin Li +3 more
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“Performance evaluation of automatic image annotation”
2012 IEEE International Conference on Computational Intelligence and Computing Research, 2012Automatic image annotation is the process of assigning keywords to digital images depending on the content information. Automatically assigning keywords to images is of great interest as it allows one to index, retrieve, and understand large collections of image data. Many techniques have been proposed for image annotation in the last decade that gives
Miss. Hemlata Sahu +2 more
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Exploiting ontologies for automatic image annotation
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, 2005Automatic image annotation is the task of automatically assigning words to an image that describe the content of the image. Machine learning approaches have been explored to model the association between words and images from an annotated set of images and generate annotations for a test image.
Munirathnam Srikanth +3 more
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Automatic medical image annotation and retrieval
Neurocomputing, 2008The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image retrieval method for a special medical image retrieval problem where the images in the retrieval database can be annotated into one of the pre-defined labels. Even more, a user may query the database with an
Jian Yao +4 more
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Automatic and Semi-Automatic Techniques for Image Annotation
2011When retrieving images, users may find it easier to express the desired semantic content with keywords than visual features. Accurate keyword retrieval can only occur when images are completely and accurately described. This can be achieved either through laborious manual effort or automated approaches.
Biren Shah +3 more
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Automatic image annotation using semantic relevance
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service, 2013Due to the semantic gap between low-level visual feature and high-level semantic concept, image annotation plays an important role in image retrieval. In this paper, an automatic image annotation approach using semantic relevance is proposed. It constructs an improved probabilistic model to characterize different regions' contributions to the semantics
Peng Zhao +3 more
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Hierarchical classification for automatic image annotation
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, 2007In this paper, a hierarchical classification framework has been proposed for bridging the semantic gap effectively and achieving multi-level image annotation automatically. First, the semantic gap between the low-level computable visual features and users' real information needs is partitioned into four smaller gaps, and multiple approachesallare ...
Jianping Fan, Yuli Gao, Hangzai Luo
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