The panelists have all served as PIs or Co-PIs on NSF REU projects in computing. They will present their REU research problems, highlight challenges they encountered, and present their results. They will also discuss what they have done, or what can be done, to incorporate such research problems within the regular computing curriculum, for ex- ample, in capstone courses or senior projects. A signi cant amount of time will be set aside for audience participation and discussion.

The relationship between color and perceived depth for realistic, colored objects with varying shading was explored. Background: Studies have shown that warm-colored stimuli tend to appear nearer in depth than cool-colored stimuli. The majority of these studies asked human observers to view physically equidistant, colored stimuli and compare them for relative depth. However, in most cases, the stimuli presented were rather simple: straight colored lines, uniform color patches, point light sources, or symmetrical objects with uniform shading. Additionally, the colors were typically highly saturated. Although such stimuli are useful for isolating and studying depth cues in certain contexts, they leave open the question of whether the human visual system operates similarly for realistic objects. Method: Participants were presented with all possible pairs from a set of differently colored objects and were asked to select the object in each pair that appears closest to them. The objects were presented on a standard computer screen, against 4 different uniform backgrounds of varying intensity. Results: Our results show that the relative strength of color as a depth cue increases when the colored stimuli are presented against darker backgrounds and decreases when presented against lighter backgrounds. Conclusion: Color does impact our depth perception even though it is a relatively weak indicator and is not necessarily the overriding depth cue for complex, realistic objects. Application: Our observations can be used to guide the selection of color to enhance the perceived depth of objects presented on traditional display devices and newer immersive virtual environments.

The phenomenon of warmer colors appearing nearer in depth to viewers than cooler colors has been studied extensively by psychologists and other vision researchers. The vast majority of these studies have asked human observers to view physically equidistant, colored stimuli and compare them for relative depth. However, in most cases, the stimuli presented were rather simple: straight colored lines, uniform color patches, point light sources, or symmetrical objects with uniform shading. Additionally, the colors used were typically highly saturated. Although such stimuli are useful in isolating and studying depth cues in certain contexts, they leave open the question of whether the human visual system operates similarly for realistic objects. This paper presents the results of an experiment designed to explore the color-depth relationship for realistic, colored objects with varying shading and contours.

We introduce the concept of perceptually meaningful image editing and present two techniques for manipulating the apparent depth of objects in an image. The user loads an image, selects an object and specifies whether the object should appear closer or further away. The system automatically determines target values for the object and/or background that achieve the desired depth change. These depth editing operations, based on techniques used by traditional artists, manipulate either the luminance or color temperature of different regions of the image. By performing blending in the gradient domain and reconstruction with a Poisson solver, the appearance of false edges is minimized. The results of a preliminary user study, designed to evaluate the effectiveness of these techniques, are also presented.

We apply simplified image-based lighting methods to reduce the equipment, cost, time, and specialized skills required for high-quality photographic lighting of desktop-sized static objects such as museum artifacts. We place the object and a computer-steered moving-head spotlight inside a simple foam-core enclosure, and use a camera to quickly record low-resolution photos as the light scans the box interior. Optimization guided by interactive user sketching selects a small set of frames whose weighted sum best matches the target image. The system then repeats the lighting used in each of these frames, and constructs a high resolution result from re-photographed basis images. Unlike previous image-based relighting efforts, our method requires only one light source, yet can achieve high resolution light positioning to avoid multiple sharp shadows. A reduced version uses only a hand-held light, and may be suitable for battery-powered, field photography equipment that fits in a backpack.

The primary goal of this research is to develop a perception based image editing system. The input to this system will be either a rendered image, a photograph, or a high dynamic range image. We are currently developing techniques that allow the user to edit these images in a perceptually intuitive manner. Specifically we are considering the following image editing features: (1) Warm-cool image adjustment, (2) Intensity adjustment, (3) Contrast adjustment, and (4) Detail adjustment. The algorithms we are developing can be used either in an interactive editing system or for automatic image adjustment.

This paper presents several methods for shading meshes from scanned paint samples that represent dark to light transitions. Our techniques emphasize artistic control of brush stroke texture and color. We first demonstrate how the texture of the paint sample can be separated from its color gradient. We demonstrate three methods, two real-time and one off-line, for producing rendered, shaded images from the texture samples. All three techniques use texture synthesis to generate additional paint samples. Finally, we develop metrics for evaluating how well each method achieves our goal in terms of texture similarity, shading correctness and temporal coherence.

This paper presents several methods for shading meshes from scanned paint samples that represent dark to light transitions. Our techniques emphasize artistic control of brush stroke texture and color. We first demonstrate how the texture of the paint sample can be separated from its color gradient. We demonstrate three methods, two real-time and one off-line for producing rendered, shaded images from the texture samples. All three techniques use texture synthesis to generate additional paint samples. Finally, we develop metrics for evaluating how well each method achieves our goal in terms of texture similarity, shading correctness and temporal coherence.

Image signal processing depends on computation intensive programs, which include the repetition of sequences of operations coded as nested loops. An effective technique in increasing the computing performance of such applications is the design and use of Application Specific Integrated Circuits using loop transformation techniques, and in particular, multidimensional (MD) retiming. The MD-retiming method improves the instruction-level parallelism of uniform loops. While many have written about the multi-dimensional retiming technique, no results have been published on the possible limitations of its application. This paper presents an analysis of that technique and its constraints when applied to nested loops with known index bounds, such as those found in two and three dimensional image processing.