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

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

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

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

—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

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

Graphics processing units (GPUs) provide large computational power at a very low price, which position GPUs well as an ubiquitous accelerator. However, GPUs are space constrained, and hence applications developed for GPUs are space sensitive. Space-constrained computational devices such as GPUs can greatly benefit from representations that reduce space consumption drastically. One such representation is the succinct representation of trees. Succinct representation of trees generally allows for operations such as parent queries, least common ancestor queries, and so on. Mapping such a robust representation to the GPU for targeted applications can lead to substantial improvement in problem sizes that are processed at a given point of time. Space-saving methods such as succinct data structures remain largely unexplored on the GPU. In this work, a succinct representation of ordered trees on the GPU is explored, with application to discrete range searching (DRS). Based on the succinct representations found applicable, a space--saving solution for DRS is presented here. In our method, DRS is mapped to a least common ancestor query on a Cartesian tree. For space-efficient DRS queries, we store the succinct representation of the Cartesian tree of an array. Our method uses a maximum of 7.5 bits of additional space per element. Furthermore, the speed-up achieved by our method is in the range of 20--25 for preprocessing and 25--35 for batch querying over a sequential implementation. Compared to an 8-threaded implementation, our preprocessing and querying methods obtain a speed-up of 6--8. We also study the applications of the DRS on the GPU. Efficient primitives expand the range of applications performed on the GPU. DRS is one such primitive with direct applications to string processing, document and text retrieval systems, and least common ancestor queries. We suggest that graph algorithms that use the least common ancestor, can be enabled on the GPU based on DRS primitive. We also show some applications of DRS in tree queries and string querying.

Abstract

Browsers of personal digital photographs all essentially fol-low the slide show paradigm, sequencing through the pho-tos in the order they are taken. A more engaging way tobrowse personal photographs, especially of a large space likea popular monument, should involve the geometric contextof the space. In this paper, we present ageometry directedphoto browserthat enables users to browse their personalpictures with the underlying geometry of the space to guidethe process. The browser uses a pre-computed package ofgeometric information about the monument for this task.The package is used to register a set of photographs takenby the user with the common geometric space of the monu-ment. This involves localizing the images to the monumentspace by computing the camera matrix corresponding to it.We use a state-of-the-art method for fast localization. Reg-istered photographs can be browsed using a visualizationmodule that shows them in the proper geometric contextwith respect to a point-based 3D model of the monument.We present the design of the geometry-directed browser anddemonstrate its utility for a few sequences of personal im-ages of well-known monuments. We believe personal photobrowsers can provide an enhanced sense of one’s own ex-perience with a monument using the underlying geometriccontext of the monument.

Abstract

Displays have seen much improvements over the years, withenhancements in spatial resolution and vertical refresh, etc.,to provide better and smoother visual experiences. Color in-tensity resolution, however, has not changed much over thepast few decades. Most displays are still limited to 8-bitsper channel. Simultaneously, much work has gone into cap-turing high dynamic range images. Mapping these directlyto current displays loses information that may be critical tomany applications. We present a way to enhance intensityresolution of a given display by mixing intensities over spa-tial or temporal domains. Our system sacrifices high verticalrefresh and spatial resolution in order to gain intensity res-olution. We present three ways to mix intensities: spatially,temporally and spatio-temporally. The systems produce in-between-intensities not present on the base display, whichare clearly distinguishable by the naked eye. We evaluateour systems using both a camera and human subjects, eval-uating whether they scale the intensity resolution and alsoensuring that the newly generated intensities follow the dis-play model

Abstract

We present a scheme for interactive ray tracing of Bezier bicubicpatches using Newton iteration in this paper. We use a mixed hi-erarchy representation as the acceleration structure. This has abounding volume hierarchy above the patches and a fixed depthsubpatch tree below it. This helps reduce the number of ray-patchintersections that needs to be evaluated and provides good initial-ization for the iterative step, keeping the memory requirements low.We use Newton iteration on the generated list of ray patch intersec-tions in parallel. Our method can exploit the cores of the CPU andthe GPU with OpenMP on the CPU and CUDA on the GPU bysharing work between them according to their relative speeds. Adata parallel framework is used throughout starting with a list ofrays, which is transformed to a list of ray-patch intersections bytraversal and then to intersections and a list of secondary rays byroot finding. Shadow and reflection rays can be handled exactly inthe same manner as a result. We also show how our method ex-tends easily to generate soft shadows using area light sources andpath tracing by tracing a large number of rays per pixel. We rendera million pixel image of the Teapot model at 125 fps on a systemwith an Intel i7 920 and a Nvidia GTX580 for primary rays onlyand at about 65 fps with one pass of shadow and refection rays.