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—Closed or nearly closed regions are an important form of perceptual structure arising both in natural imagery and in many forms of human-created imagery including sketches, line art, graphics, and formal drawings. This paper presents an effective algorithm especially suited for finding perceptually salient, compact closed region structure in hand-drawn(More)
A <italic>Collaborage</italic> is a collaborative collage of physically represented information on a surface that is connected with electronic information, such as a physical In/Out board connected to a people-locator database. The physical surface (board) contains items that are tracked by camera and computer vision technology. Events on the board trigger(More)
We present a user interface design for labeling elements in document images at a pixel level. Labels are represented by overlay color, which might map to such terms as " handwriting " , " machine print " , " graphics " , etc. The primary purpose is to streamline processes for manual production of groundtruth data, which is necessary for training algorithms(More)
This paper shows how techniques from computational vision can be deployed to support interactive sketch editing. While conventional computer-supported drawing tools give users access to visible marks or image objects at a single level of abstraction , a human user's visual system rapidly constructs complex groupings and associations among image elements(More)
The human visual system makes a great deal more of images than the elemental marks on a surface. In the course of viewing, creating, or editing a picture, we actively construct a host of visual structures and relationships as components of sensible interpretations. This paper shows how some of these computational processes can be incorporated into(More)
This paper presents a novel image editing program emphasizing easy selection and manipulation of material found in informal, casual documents such as sketches, handwritten notes, whiteboard images, screen snapshots, and scanned documents. The program, called <i>ScanScribe</i>, offers four significant advances. First, it presents a new, intuitive model for(More)
This paper introduces the use of the Multiple Cause Mixture Model to automatic text category assignment. Although much research has been done on text categorization, this algorithm is novel in that is unsupervised, that is, does not require pre-labeled training examples , and it can assign multiple category labels to documents. In this paper we present very(More)