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ImageRover On-Line Demo

Select an initial set of Images by Keywords

Initially the user is asked to enter a set of keywords in order to start from a relevant set of images. When the user enters the keywords that he/she thinks are related to the image, an appropriate set of images is fetched from the database by using only LSI vectors. This is called the page 0.

Guide Search via Query by Example

ImageRover employs a query by example paradigm. Search is guided by relevance feedback from the user. ImageRover gets the search going by displaying a set images derived by the page 0. To guide a search, select relevant example images from those presented.

To select a relevant image, mark the check-box found next to the relevant image(s)...

ImageRover formulates a query based on the composition of colors, the dominant orientations, and the semantic associations present in the user-selected example images. Efforts are currently underway to improve accuracy of ImageRover by the use of modular eigenspaces and modeling by various LSI subject categories.

By specifying multiple relevant images, you can usually increase the chances for better results. If only one example is chosen, then ImageRover will conduct a search based on semantic distribution only.

Initiate a Search via the Search Button

Once you find and mark one or more images to guide the search, initiate a query by clicking on the search button.

View the Results of a Query

After a query, your selected relevant image(s) are shown in the top of the screen.

ImageRover will display what it believes are the most similar images in the index based on color, orientation and textual statistics of the relevant images you selected. The retreived images are displayed left to right and top to bottom, with the most similar image shown first, etc.

Iteratively Refine the Query

Once a search has been initiated, you can then select other relevant images to guide next search and/or deselect one or more of the query images and iterate the query. There is no limit to the number of iterations in providing relevance feedback, nor in the number of example images.

In a typical search, a user starts the session by specifying a set of keywords related to the images which he/she intends to search for. When the user finds something similar to what he/she is looking for, he/she checks the corresponding check-box and asks the system for similar images. The system usually retrieves relevant images and false matches, the user checks the images that are more relevant with respect to what he/she is looking for and reiterates the query until desired images are found. During a search, the user can deselect one or more of the example images and check some other images he/she finds more relevant.

Visit WWW Documents via Clicking on Thumbnail Images

Each displayed thumbnail image is a hypertext link to the original image. By clicking on any thumbnail, you can retrieve the desired image from its corresponding home web site.

Control Search Accuracy/Speed via the Seach Accuracy Button

Through the search accuracy button, you can specify the desired level of approximation factor employed in the k-nearest neighbors algorithm. Settings of ``high,'' ``medium,'' and ``low'' allow the user to control of the tradeoff between search speed/accuracy.

Try On-Line Demo

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© 1996-1998 Image and Video Computing Group - Boston University
Last Modified: April 20, 1998