We present design principles for creating effective assembly instructions and a system that is based on these principles. The principles are drawn from cognitive psychology research which investigated people's conceptual models of assembly and effective methods to visually communicate assembly information. Our system is inspired by earlier work in robotics on assembly planning and in visualization on automated presentation design. Although other systems have considered presentation and planning independently, we believe it is necessary to address the two problems simultaneously in order to create effective assembly instructions. We describe the algorithmic techniques used to produce assembly instructions given object geometry, orientation, and optional grouping and ordering constraints on the object's parts. Our results demonstrate that it is possible to produce aesthetically pleasing and easy to follow instructions for many everyday objects.
Input: 3 MLIC ImagesOur Results: Enhanced Shape and Surface Detail AbstractWe present a new image-based technique for enhancing the shape and surface details of an object. The input to our system is a small set of photographs taken from a fixed viewpoint, but under varying lighting conditions. For each image we compute a multiscale decomposition based on the bilateral filter and then reconstruct an enhanced image that combines detail information at each scale across all the input images. Our approach does not require any information about light source positions, or camera calibration, and can produce good results with 3 to 5 input images. In addition our system provides a few high-level parameters for controlling the amount of enhancement and does not require pixel-level user input. We show that the bilateral filter is a good choice for our multiscale algorithm because it avoids the halo artifacts commonly associated with the traditional Laplacian image pyramid. We also develop a new scheme for computing our multiscale bilateral decomposition that is simple to implement, fast O(N 2 log N) and accurate.
We seek to recolor the input image (a). However, changing the color (reflectance) of the shirt alone, without modifying the illumination, does not account for the correct diffuse reflection on the girl's arm or interreflections in the fine texture of the shirt (b). Indeed, the image in (b) still has bluish reflections on the arm and a purple color shift on the shirt. Our user-assisted decomposition ( Figure 2) lets us modify indirect illumination to match the modified shirt color (c), leading to a much more consistent and natural looking recoloring. AbstractChanging the color of an object is a basic image editing operation, but a high quality result must also preserve natural shading. A common approach is to first compute reflectance and illumination intrinsic images. Reflectances can then be edited independently, and recomposed with the illumination. However, manipulating only the reflectance color does not account for diffuse interreflections, and can result in inconsistent shading in the edited image. We propose an approach for further decomposing illumination into direct lighting, and indirect diffuse illumination from each material. This decomposition allows us to change indirect illumination from an individual material independently, so it matches the modified reflectance color. To address the underconstrained problem of decomposing illumination into multiple components, we take advantage of its smooth nature, as well as user-provided constraints. We demonstrate our approach on a number of examples, where we consistently edit material colors and the associated interreflections.Links: DL PDF WEB
Figure 1: A general purpose online map (from Google Maps) with fixed scale is not an effective destination map because the neighborhood streets disappear. Our system selects a relevant subset of the highways, arterials and residential roads required to reach the destination. It then lays out the selected roads, so that all the selected roads are visible and renders the map in a hand-drawn style.
Figure 1: Interactive furniture layout. For a given layout (left), our system suggests new layouts (middle) that respect the user's constraints and follow interior design guidelines. The red chair has been fixed in place by the user. One of the suggestions is shown on the right. AbstractWe present an interactive furniture layout system that assists users by suggesting furniture arrangements that are based on interior design guidelines. Our system incorporates the layout guidelines as terms in a density function and generates layout suggestions by rapidly sampling the density function using a hardware-accelerated Monte Carlo sampler. Our results demonstrate that the suggestion generation functionality measurably increases the quality of furniture arrangements produced by participants with no prior training in interior design.
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