Abstract

We present an approach to simulate both Newto-nian and generalized Newtonian fluids using Lattice BoltzmannMethod. The focus has been on accurately modelling non-Newtonian fluids at the micro channel level from biological fluidsin the past. Our method can model macroscopic behaviour of suchfluids by simulating the variation of properties such as viscositythrough the bulk of the fluid. The method works regardless ofthe magnitude of flow, be it through a thin tube or a largequantity of liquid splashing in a container. We simulate thechange in viscosity of a generalized Newtonian fluid and its freesurface interactions with obstacles and boundaries. We harnessthe inherent parallelism of Lattice Boltzmann Method to give afast GPU implementation for the same

Abstract

—Traditional video editing interfaces model and represent videos as a collection of frames against a timeline, which makes object-centric manipulation of videos a laborious task. We enable simple and meaningful interaction for object-centric navigation and manipulation of long shot videos, by introducing operators on three high-level video semantics: background mosaics, object motions, and camera motions. We estimate the scene background and represent the object motion using 3D space-time trajectories. We use the 3D object trajectories as basic interaction elements and define several object and camera operations as simple and intuitive curve manipulations. These allow users to perform various video object temporal manipulations by interactively manipulating the object trajectories. The camera operations model the camera as a movable and scalable aperture and allow the users to simulate pan, tilt, and zoom effects by creating new camera trajectories. With several example compositions we demonstrate that our representation and operations allow users to simply and interactively perform numerous seemingly complex, high-level video manipulation tasks.

Abstract

Divide and Conquer Ray Tracing (DACRT) is a recent technique which constructs no explicit acceleration structure. It creates and traverses an implicit hierarchy in a depth-first fashion recursively and is suited for dynamic scenes that change constantly. In this paper, we present a parallel version of DACRT that runs entirely on the GPU, which exploits efficient primitives like sort and reduce. Our approach suits the GPU well, with a low memory footprint. Our implementation outperforms the serial CPU algorithm for both primary and secondary ray passes. We show good performance on primary pass and on advanced effects.

Abstract

String sorting or variable-length key sorting has lagged in performance on the GPU even as the fixed-length key sorting has improved dramatically. Radix sorting is the fastest on the GPUs. In this paper, we present a fast and efficient string sort on the GPU that is built on the available radix sort. Our method sorts strings from left to right in steps, moving only indexes and small prefixes for efficiency. We reduce the number of sort steps by adaptively consuming maximum string bytes based on the number of segments in each step. Performance is improved by using Thrust primitives for most steps and by removing singleton segments from consideration. Over 70% of the string sort time is spent on Thrust primitives. This provides high performance along with high adaptability to future GPUs. We achieve speed of up to 10 over current GPU methods, especially on large datasets. We also scale to much larger input sizes. We present results on easy and difficult strings defined using their after-sort tie lengths.

Abstract

We present an approach to simulate both Newtonian and generalized Newtonian fluids using Lattice Boltzmann Method. The focus has been on accurately modelling nonNewtonian fluids at the micro channel level from biological fluids in the past. Our method can model macroscopic behaviour of such fluids by simulating the variation of properties such as viscosity through the bulk of the fluid. The method works regardless of the magnitude of flow, be it through a thin tube or a large quantity of liquid splashing in a container. We simulate the change in viscosity of a generalized Newtonian fluid and its free surface interactions with obstacles and boundaries. We harness the inherent parallelism of Lattice Boltzmann Method to give a fast GPU implementation for the same.

Abstract

We present an approach for fast registration of a Global Articulated 3D Model to RGBD data from Kinect. Our approach uses geometry based matching of rigid parts of the articulated objects in depth images. The registration is performed in a parametric space of transformations independently for each segment. The time for registering each frame with the global model is reduced greatly using this method. We experimented the algorithm with different articulated object datasets and obtained significantly low execution time as compared to ICP algorithm when applied on each rigid part of the articulated object.

Abstract

Global optimization of MRF energy using graph cuts iswidely used in computer vision. As the images are gettinglarger, faster graph cuts are needed without sacrificing op-timality. Initializing or reparameterizing a graph using re-sults of a similar one has provided efficiency in the past. Inthis paper, we present a method to speedup graph cuts us-ing shrink-expand reparameterization. Our scheme mergesthe nodes of a given graph to shrink it. The resulting graphand its mincut are expanded and used to reparameterize theoriginal graph for faster convergence. Graph shrinking canbe done in different ways. We use a block-wise shrinkingsimilar to multiresolution processing of images in our Mul-tiresolution Cuts algorithm. We also develop a hybrid ap-proach that can mix nodes from different levels without af-fecting optimality. Our algorithm is particularly suited forprocessing large images. The processing time on the fulldetail graph reduces nearly by a factor of 4. The overallapplication time including all book-keeping is faster by afactor of 2 on various types of images

Abstract

Displays remain flat and passive amidst the many changes in their fundamental technologies. One natural step ahead is tocreate displays that merge seamlessly in shape and appearance with one’s natural surroundings. In this paper, we present a system todesign, render to, and build view-dependentmultiplanar displaysof arbitrary piecewise-planar shapes, built using polygonal facets.Our system provides high quality, interactive rendering of 3D environments to a head-tracked viewer on arbitrary multiplanar displays.We develop a novel rendering scheme that produces exact image and depth map at each facet, producing artifact-free images on andacross facet boundaries. The system scales to a large number of display facets by rendering all facets in a single pass of rasterization.This is achieved using a parallel, perframe, view-dependent binning and prewarping of scene triangles. The display is driven using oneor more targetquilt imagesinto which facet pixels are packed. Our method places no constraints on the scene or the display and allowsfor fully dynamic scenes to be rendered interactively at high resolutions. The steps of our system are implemented efficiently oncommodity GPUs. We present a few prototype displays to establish the scalability of our system on different display shapes, formfactors, and complexity: from a cube made out of LCD panels to spherical/cylindrical projected setups to arbitrary complex shapes insimulation. Performance of our system is demonstrated for both rendering quality and speed, for increasing scene and display facetsizes. A subjective user study is also presented to evaluate the user experience using a walk-around display compared to a flat panelfor a game-like setting.

Abstract

Matching patches of a source image with patches of itself ora target image is a first step for many operations. Finding the optimumnearest-neighbors of each patch using a global search of the image isexpensive. Optimality is often sacrificed for speed as a result. We presentthe Mixed-Resolution Patch-Matching (MRPM) algorithm that uses apyramid representation to perform fast global search. We compare mixed-resolution patches at coarser pyramid levels to alleviate the effects ofsmoothing. We store more matches at coarser resolutions to ensure widersearch ranges and better accuracy at finer levels. Our method achievesnear optimality in terms of average error compared to exhaustive search.Our approach is simple compared to complex trees or hash tables used byothers. This enables fast parallel implementations on the GPU, yieldingupto 70×speedup compared to other iterative approaches. Our approachis best suited when multiple, global matches are needed

Abstract

Large scale reconstructions of camera matrices and pointclouds have been created using structure from motion from communityphoto collections. Such a dataset is rich in information; it representsa sampling of the geometry and appearance of the underlying space.In this paper, we encode the visibility information between and amongpoints and cameras asvisibility probabilities. The conditional visibilityprobability of a set of points on a point (or a set of cameras on a camera)can rank points (or cameras) based on their mutual dependence. Wecombine the conditional probability with a distance measure to prioritizepoints for fast guided search for the image localization problem. Wedefine dual problem of feature triangulation as finding the 3D coordinatesof a given image feature point. We use conditional visibility probabilityto quickly identify a subset of cameras in which a feature is visible