Visual structures for image browsing (original) (raw)

2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004

In any CBIR system, visualization is important, either to show the final result to the user or to form the basis for interaction. Advanced systems use 2-dimensional similarity based visualization which show not only the information of one image itself but also the relations between images. A problem in interactive 2D visualization is the overlap between the images displayed. This obviously reduces the search capability. Simply spreading the images on the screen space will not preserve the relations between them. In this paper, we propose a visualization scheme which reduces the overlap as well as preserves the general distribution of the images displayed. Results show that an effective balance between display of structures and limited overlap can be achieved.

Interactive access to large image collections using similarity-based visualization

Journal of Visual Languages and Computing, 2008

Image collections are getting larger and larger. To access those collections, systems for managing, searching, and browsing are necessary. Visualization plays an essential role in such systems. Existing visualization systems do not analyze all the problems occurring when dealing with large visual collections. In this paper, we make these problems explicit. From there, we establish three general requirements: overview, visibility, and structure preservation. Solutions for each requirement are proposed, as well as functions balancing the different requirements. We present an optimal visualization scheme, supporting users in interacting with large image collections. Experimental results with a collection of 10,000 Corel images, using simulated user actions, show that the proposed scheme significantly improves performance for a given task compared to the 2D grid-based visualizations commonly used in content-based image retrieval. r (M. Worring). museum archives, and to scientific pictures in medicine, astronomy, or biology. Hence, large image collections are common everywhere.

Presenting and visualizing results on an image retrieval user interface

Electronic Workshops in Computing, 2017

The volume of images available online has increased significantly but the choices offered by image retrieval systems have not kept pace. We describe the design and evaluation of a 'high density' image search interface focusing on the results pages. We quantitatively and qualitatively compared image presentation on a high density interface with a traditional image search interface. Our results show that users had major problems with high-density interfaces for images due to information overload. We point to further work which could improve the user experience.

User interfaces: a bridge for the semantic gap in image retrieval systems

The field of content based image retrieval has experienced a lot of advances. These are evidenced by the number of research publications that present new techniques of image feature representation, image indexing and similarity estimation. While all these are important core techniques, they remain methods for implementing systems. There is a relatively less emphasis on the role of user interfaces through which the users and the image retrieval systems interact. In this work, we present an overview of the work that has been carried out in the area of user interfaces for image retrieval systems. Finally we present some recommendations for the direction of research in the field of designing image retrieval system interfaces.

Interactive content-based visualizations for multimedia search

2017

Finding images or videos in multimedia collections is a difficult task. Many collections only have metadata such as filenames or timestamps, and no other information is available. To augment this, we can employ content based analysis techniques that provides extra content based metadata. This provides a good starting point, but the accuracy is often insufficient to automate full collection categorization. A human in the loop is essential to aid with search and categorization. In this thesis we evaluate how to retrieve elements from multimedia collections for a variety of retrieval tasks. We investigate different user interfaces that extend content based retrieval methods with novel user interface techniques. In one interface, MediaTable, we focus on categorization tasks by leveraging table-style user interfaces with images so users can investigate both the multimedia content and associated metadata at the same time. Users can categorize elements by placing them in buckets, and we pe...

Visual information retrieval for the web

2001

paper we present the conception and the evaluation of a visual information retrieval system for the Web. Our work has been motivated by the lack of good user interfaces assisting the user in searching the Web. The selected visualisations and the reasons why they have been chosen are explained in detail. An evaluation of these visualisa- tions as an add-on to the traditional result list is presented.

Content-based image visualisation

The proliferation of content-based image retrieval techniques has highlighted the need to understand the relationship between image clustering based on low-Ievel image features and image clustering made by human users. In conventional image retrieval systems, images are typically characterized by a range offeatures such as color, texture, and shape. However, little is known to what extent these low-Ievel features can be effectively combined with information visualization techniques such that users may explore images in a digital library according to visual similarities. In this article, we compared and analyzed a number of Pathfinder networks of images generated based on such features. Salient structures of images are visualized according to features extracted .from color, texture, and shape orientation. Implications for visualizing and constructing hypermedia systems are discussed.

Content-based image visualization

… , 2000. Proceedings. IEEE …, 2000

Similarity-based image browsing

Proceedings of the 16th IFIP World …, 2000

Digital images and videos have an increasingly important role in today's telecommunication and our everyday life in modern information society. The past few years witnessed a proliferation of content-based image retrieval techniques. Images are typically characterized by intrinsic attributes of images such as color, texture, and shape. However, the potential of integrating these techniques with visualization and data-mining techniques has yet been fully explored. Users should be able to explore images in a database or video clips by visual similarities. In this article, we explore the synergy between Pathfinder networks and content-based information retrieval techniques. Salient structures of images are revealed through visualization models derived from features extracted from images. Visualizations are generated from three feature classes of the well-known QBIC system: color, layout, and texture.

A Browsing Approach to Explore Web Image Search Results

2019

Image objects are frequently used online available multimedia content due to their extensive information delivering power. The rapid development of image search engines fulfills the user's image information needs. Traditionally the unsatisfactory linear presentations of image results often lead issues mainly related to browsing, exploration, and visualization. The exploration of image results allows us to navigate, organize, and compare the results. Navigation mainly involves browsing, which will enable users to find the desired image results satisfactorily. Due to the linear presentation and browsing approaches, the current image results exploration is inefficient. In this research, an approach is proposed to browse and explore image results while reducing the associated reachability issues. The approach utilizes the multimodal graph for non-linear exploration of web image results. The similarity relationships in the graph are further exploited to partition the groups into multiple clusters, whereas multimodal similarity relationship deals with textual and visual information associated with image results. Moreover, a search tool is also built to provide an interactive search user interface design to explore the image results in a usable way.

Visual structures for image browsing (original) (raw)

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