2282922
Estimation of 3D Surface Shape and Smooth Radiance from 2D Images: A Level Set Approach
We cast the problem of shape reconstruction of a scene as the global region segmentation of a collection of calibrated images. We assume that the scene is composed of a number of smooth surfaces and a background, both of which support smooth Lambertian radiance functions. We formulate the problem in a variational framework, where the solution (both the shape and radiance of the scene) is a minimizer of a global cost functional which combines a geometric prior on shape, a smoothness prior on radiance and a data fitness score. We estimate the shape and radiance via an alternating minimization: The radiance is computed as the solutions of partial differential equations defined on the surface and the background. The shape is estimated using a gradient descent flow, which is implemented using the level set method. Our algorithm works for scenes with smooth radiances as well as fine homogeneous textures, which are known challenges to traditional stereo algorithms based on local correspondence.
2927787
Real-time virtual object insertion
We present a system to insert virtual objects into real image sequences in real time. The system consists of offthe- shelf hardware (a camera connected to a Pentium PC) and software to (a) automatically select and track region features despite changes in illumination, (b) estimate threedimensional position and orientation of surface patches relative to an inertial reference frame despite individual pointfeatures appearing and disappearing, (c) insert a texturemapped virtual object into the scene so as to make it appear to be part of the scene and moving with it. This is all done in real time. The multi-thread C++ code, which is readily interfaced with a frame grabber as well as Matlab for development, will be made available to the public at the demonstration.
6346856
Real-Time Feature Tracking and Outlier Rejection with Changes in Illumination
We develop an efficient algorithm to track point features supported by image patches undergoing aflne deformations and changes in illumination. The algorithm is based on a combined model of geonietty and photometry that is used to track features as well as to detect outliers in a hypothesis testing framework. The algorithm runs in real time on a personal computer, and is available to the public.
121904888
Shedding light on stereoscopic segmentation
We propose a variational algorithm to jointly estimate the shape, albedo, and light configuration of a Lambertian scene from a collection of images taken from different vantage points. Our work can be thought of as extending classical multi-view stereo to cases where point correspondence cannot be established, or extending classical shape from shading to the case of multiple views with unknown light sources. We show that a first naive formalization of this problem yields algorithms that are numerically unstable, no matter how close the initialization is to the true geometry. We then propose a computational scheme to overcome this problem, resulting in provably stable algorithms that converge to (local) minima of the cost functional. Although we restrict our attention to Lambertian objects with uniform albedo, extensions of our framework are conceivable.
14241332
Visual tracking in the presence of motion blur
We consider the problem of visual tracking of regions of interest in a sequence of motion blurred images. Traditional methods couple tracking with deblurring in order to correctly account for the effects of motion blur. Such coupling is usually appropriate, but computationally wasteful when visual tracking is the lone objective. Instead of deblurring images, we propose to match regions by blurring them. The matching score for two image regions is governed by a cost function that only involves the region deformation parameters and two motion blur vectors. We present an efficient algorithm to minimize the proposed cost function and demonstrate it on sequences of real blurred images.
15692724
Region-Based Segmentation on Evolving Surfaces with Application to 3D Reconstruction of Shape and Piecewise Constant Radiance
We consider the problem of estimating the shape and radiance of a scene from a calibrated set of images under the assumption that the scene is Lambertian and its radiance is piecewise constant. We model the radiance segmentation explicitly using smooth curves on the surface that bound regions of constant radiance. We pose the scene reconstruction problem in a variational framework, where the unknowns are the surface, the radiance values and the segmenting curves. We propose an iterative procedure to minimize a global cost functional that combines geometric priors on both the surface and the curves with a data fitness score. We carry out the numerical implementation in the level set framework.
15922848
The Stanford Microarray Database
The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77-80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73-76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10-14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332-333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45-48] and can be accessed at http://genome-www.stanford.edu/microarray.
20588758
Cluster computing
Cluster computing can be described as a fusion of the fields of parallel, high-performance, distributed, and high-availability computing. Cluster computing has become a hot topic of research among academic and industry community including system designers, network developers, language designers, standardizing forums, algorithm developers, graduate students and faculties. The use of clusters as computing platform is not just limited to scientific and engineering applications; there are many business applications that can benefit from the use of clusters. There are many exciting areas of development in cluster computing with new ideas as well as hybrids of old ones being deployed for production as well as research systems. The aim of this special issue is to bring together original and latest work from both academia and industry on various issues related to cluster computing. This research, and development, is being done in many areas but there are a few that are of special interest. The first one is, with no doubt, the network. Clusters are based on the communication between nodes and designing fast and low latency networks is a must for clusters to become the configuration of the future. Plenty of work being done in this are in
8032236
First story detection in TDT is hard
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