Abstract—Motion blur due to camera motion can significantly degrade the quality of an image. Since the path of the camera motion can be arbitrary, deblurring of motion blurred images is a hard problem. Previous methods to deal with this problem have included blind restoration of motion blurred images, optical correction using stabilized lenses, and special CMOS sensors that limit the exposure time in the presence of motion. In this paper, we exploit the fundamental trade off between spatial resolution and temporal resolution to construct a hybrid camera that can measure its own motion during image integration. The acquired motion information is used to compute a point spread function (PSF) that represents the path of the camera during integration. This PSF is then used to deblur the image. To verify the feasibility of hybrid imaging for motion deblurring, we have implemented a prototype hybrid camera. This prototype system was evaluated in different indoor and outdoor scenes using long exposures and complex camera motion paths. The results show that, with minimal resources, hybrid imaging outperforms previous approaches to the motion blur problem. We conclude with a brief discussion on how our ideas can be extended beyond the case of global camera motion to the case where individual objects in the scene move with different velocities. Index Terms—Sharpening and deblurring, inverse filtering, motion, motion blur, point spread function, resolution, hybrid imaging. 1

Video matting is the process of pulling a high-quality alpha matte and foreground from a video sequence. Current techniques require either a known background (e.g., a blue screen) or extensive user interaction (e.g., to specify known foreground and background elements) . The matting problem is generally under-constrained, since not enough information has been collected at capture time. We propose a novel, fully autonomous method for pulling a matte using multiple synchronized video streams that share a point of view but differ in their plane of focus. The solution is obtained by directly minimizing the error in filter-based image formation equations, which are over-constrained by our rich data stream. Our system solves the fully dynamic video matting problem without user assistance: both the foreground and background may be high frequency and have dynamic content, the foreground may resemble the background, and the scene is lit by natural (as opposed to polarized or collimated) illumination.

We present an efficient algorithm for visibility sorting a set of moving geometric objects into a sequence of image layers which are composited to produce the final image. Instead of splitting the geometry as in previous visibility approaches, we detect mutual occluders and resolve them using an appropriate image compositing expression or merge them into a single layer. Such an algorithm has many applications in computer graphics; we demonstrate two: rendering acceleration using image interpolation and visibility-correct depth of field using image blurring. We propose a new, incremental method for identifying mutually occluding sets of objects and computing a visibility sort among these sets. Occlusion queries are accelerated by testing on convex bounding hulls; less conservative tests are also discussed. Kd-trees formed by combinations of directions in object or image space provide an initial cull on potential occluders, and incremental collision detection algorithms are adapted to resolve pairwise occlusions, when necessary. Mutual occluders are further analyzed to generate an image compositing expression; in the case of nonbinary occlusion cycles, an expression can always be generated without merging the objects into a single layer. Results demonstrate that the algorithm is practical for real-time animation of scenes involving hundreds of objects each comprising hundreds or thousands of polygons.

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s and Applications, S. 277, ACM SIGGRAPH, 1999. How do we present the motion of objects in computer generated still images? Generally, we don't. Or, if we do, we use motion blurring to simulate a real-world camera [PC83]. Besides, it costs a great deal of extra rendering time, and the only thing it does is blur the objects so that their contours are unrecognizable. The goal to convey information about the movement per se is not entirely met. If, however, we consider the application of non-photorealistic rendering techniques, it is promising to adopt successful illustrative techniques from comics to depict past and future motions of objects in a single image. Presenting Motion Speedlines are an important stylistic element in comics, and although they are not based on an exact physical model, their use is well known to all of us [McC93]. Starting from the very first cartoons Little Nemo and Krazy Kat, speedlines have always depicted past motion. Another technique to illustrate the mo...

The photon map technique for global illumination does not specifically address animated scenes. In particular, prior work has not considered the problem of temporal sampling (motion blur) while using the photon map. In this paper we examine several approaches for simulating motion blur with the photon map. In particular we show that a distribution of photons in time combined with the standard photon map radiance estimate is incorrect, and we introduce a simple generalization that correctly handles photons distributed in both time and space. Our results demonstrate that this time dependent photon map extension allows fast and correct estimates of motion-blurred illumination including motion-blurred caustics. 1.

Motion provides strong visual cues for the perception of shape and depth, as demonstrated by cognitive scientists and visual artists. This paper presents a novel visualization technique -- kinetic visualization -- that uses particle systems to add supplemental motion cues which can aid in the perception of shape and spatial relationships of static objects. Based on a set of rules following perceptual and physical principles, particles flowing over the surface of an object not only bring out, but also attract attention to, essential information on the shape of the object that might not be readily visible with conventional rendering that uses lighting and view changes. Replacing still images with animations in this fashion, we demonstrate with both surface and volumetric models in the accompanying videos that in many cases the resulting visualizations effectively enhance the perception of three-dimensional shape and structure. The results of a preliminary user study that we have conducted also show evidence that the supplemental motion cues helped.

In this paper we present a novel visualization technique -- kinetic visualization -- that uses motion along a surface to aid in the perception of 3D shape and structure of static objects. The method uses particle systems, with rules such that particles flow over the surface of an object to not only bring out, but also attract attention to information on a shape that might not be readily visible with a conventional rendering method which uses lighting and view changes. Replacing still images with animations in this fashion, we demonstrate with both surface and volumetric models in the accompanying videos that in many cases the resulting visualizations effectively enhance the perception of three-dimensional shape and structure. We also describe how for both types of data a texture-based representation of this motion be rendered using PC graphics hardware for interactive visualization. Finally, the results of a user study that we have conducted is presented, which show evidence that the supplemental motion cues can be helpful.

This paper will survey most of the major issues that one must deal with when generating realistic images+. Webegin with an overviewofthe rendering process and a quick reviewofvisible surface determination algorithms. We t hen discuss, in more detail, shading, anti-aliasing, texture mapping, shadows, optical effects and close with a discussion of modeling primitives

Motion blur occurs in photography by the motion of objects during the finite exposure time that the camera shutter remains open for to record the image on film. The traditional method of rendering a motion blur with a computer is to render the scene at many discrete time instances in every frame. In this paper, we present an efficient motion blur generation method that leverages modern commodity graphics hardware. Our method avoids rendering the entire complex scene many times per frame. It first renders the scene into a texture, next renders the optic flow, created based on object transformation, to a vector field texture. The scene texture is finally efficiently blurred according to the vector field using texturemapping hardware to do a piecewise iterative line integral convolution. Though our method uses vertex velocities to calculate image pixel velocities, the line integral convolution is performed on an image, making our method largely independent of scene complexity. Keywords: