International Journal of Computer Vision
Information retrieval evaluation in practice: a case study approach
Information Processing and Management: an International Journal
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unifying textual and visual cues for content-based image retrieval on the World Wide Web
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Unifying Keywords and Visual Contents in Image Retrieval
IEEE MultiMedia
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
LabelMe: A Database and Web-Based Tool for Image Annotation
International Journal of Computer Vision
A unified framework for image retrieval using keyword and visual features
IEEE Transactions on Image Processing
Retrieving and ranking unannotated images through collaboratively mining online search results
Proceedings of the 20th ACM international conference on Information and knowledge management
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Advances in digital photography accompanied by the overwhelming usage of internet in the past few years have resulted in millions of images being uploaded on the Web (internet) every day. Most of the information is not readily accessible as the images are not organized to allow efficient browsing, searching and retrieval. The image search engines have been largely based on the annotations, as the process of image retrieval by the features and contents of the image is still in its infancy. Humans and computers have their own strengths and limitations. While the human cognitive skills limit themselves when voluminous data has to be interpreted and analyzed, computer algorithms can fail when the need for semantic knowledge is required from the image. Research in other areas has supported the claim that a hybrid computer aided and operator guided solution can potentially improve the performance of the system. Very little research has been done on the area of human computer interaction with respect to image retrieval based on annotations and image content. This paper mainly focuses on the use of human computer interaction with respect to image retrieval and also discusses the issues of semantic gap, indexing and correlation of images. A sports image data base will be used to demonstrate and evaluate our approach.