Stained Glass Collage

We originally developed stained glass visualizations as a means to summarize videos by combining regions of interest in video shots into a collage. We adapted the video-based regions of interest algorithm to find regions of interest in any kind of photo after previously using face detection to find those regions in photos with faces. The revised algorithm uses a combination of texture and color to find regions of interest even in photos without clearly detectable faces.

As users may choose the orientation and aspect ratio of a collage, we need to place the photo regions on the canvas such that the available space is covered. To fill the spaces between regions, we assign each point on the canvas to the closest photo region for which the point is inside the photo bounds. To measure the distance between a photo region and a point in the canvas, we compute the Euclidian distance between the point and the center of the photo region and subtract the radius of the ellipse enclosing the photo region. This distance measure gives larger photo regions more coverage and creates slightly curved borders between areas. This process is illustrated the figure below. A point with the same distances to the three photo regions d1, d2, and d3 lies on the border of those photo regions.

After an initial collage is generated, users may change the orientation and aspect ratio of the collage and select border thickness and color. We provide a Java applet that lets users reorder and remove images through drag-and-drop operation. Users can also change the region-of-interest by moving the handles of a bounding box. Finally, users may zoom in or out of individual images.

Technical Contact: Andreas Girgensohn

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