Content-Based Image Retrieval at the End of the Early Years
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The Perception of Visual Information, 2e
The Perception of Visual Information, 2e
Unifying Keywords and Visual Contents in Image Retrieval
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Proceedings of the tenth ACM international conference on Multimedia
The Journal of Machine Learning Research
Feature generation for text categorization using world knowledge
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
MOSIR: image and segment-based retrieval for mobile phones
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
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This paper presents a novel method for facilitating user-friendly image retrieval by attaching names to image regions. We first detect only the most prominent regions in images when such entities exist, using our own nonlinear image segmentation technique. Besides their visual features, the layout and relations between selected regions are also emphasized. Next, we apply an adaptive and multi-modal classification and naming of image regions using subsequent clustering methods to the features of the regions and related words as well as relevancy information. For both the naming and the testing, we have added a set of illustrations acting as abstract prototypes of the regions to randomly selected natural images. Experiments on 20,000 natural images show the efficacy of using this multilayer region naming model as well as of extensively interacting with users, enabling them to present their queries by a combination of region names, sketches and example images or regions.