Extending Document Exploration with Image Retrieval: Concept and First Results

Table 2 lists the results for the images of Figure 1 using RMSE, VQM, DCTune and Universal Image Quality Index in YC r C b 4:2:2 space methods.. Ripmap image is a reference

Database creation consists of texture image database, tamura feature extraction, fuzzy clustering and query terms, while database retrieval consists of visual query,

We here employ SOM for the arrangement of posture data included in motion files, and call the resulting map of pos- tures a motion map, which is used in constructing a graphical

Bifocal Radial Visualization of Intranet Search Results using Image

Figure 5: The top image shows an initial dense and clut- tered 2D scatter plot with a 35 x 35 binning grid overlay, the bottom image shows the Binned Density Map Visualization

First, we show the results of a psychophysical study compared with first-order image statistics, in an attempt to gain some understanding in what makes an image be perceived

Using this set of reference sketches we have eval- uated descriptor performance by querying the database for the most similar images to each sketch and finding the rank of the

Our system involves two main stages: the retrieval phase to determine a subset of images that are most similar to the query image and the computation of the camera’s pose.. This