322 subjects participated in an experimental study to investigate the effects of tactile, olfactory, audio and visual sensory cues on a participant's sense of presence in a virtual environment and on their memory for the environment and the objects in that environment.Results strongly indicate that increasing the modalities of sensory input in a virtual environment can increase both the sense of presence and memory for objects in the environment. In particular, the addition of tactile, olfactory and auditory cues to a virtual environment increased the user's sense of presence and memory of the environment. Surprisingly, increasing the level of visual detail did not result in an increase in the user's sense of presence or memory of the environment.

Abstract

Johnson and Hebert's spin-images have been applied to the registration of range images and object recognition with much success because they are rotation, scale, and pose invariant. In this paper we address two issues concerning spin-images, namely: (1) comparing uncompressed spinimages across large datasets is costly, and (2) a method to select the appropriate bin size and image width for spinimages is not clearly defined.Our solution to these issues is a multi-resolution method that generates a pyramid of spin-images by successively decreasing the spin-image size by powers of two. To efficiently correlate surface points, we compare spin-images in a low-to-high resolution manner. Once multi-resolution spin-images are generated for a given object, we have found that the different resolutions can also be used to compare objects that have differing or non-uniform point densities. To select the appropriate bin sizes for comparing such objects, we use the ratio of the average edge lengths of the objects. We also show preliminary results of using the pyramid to converge on the appropriate image width by traversing the pyramid in a low-to-high resolution manner looking for the highest resolution at which the fewest number of highly correlated points are found to match a given feature point.

Mappings between surfaces have a variety of uses, including texture transfer, multi-way morphing, and surface analysis. Given a 4D implicit function that defines a morph between two implicit surfaces, this article presents a method of calculating a mapping between the two surfaces. We create such a mapping by solving two PDEs over a tetrahedralized hypersurface that connects the two surfaces in 4D. Solving the first PDE yields a vector field that indicates how points on one surface flow to the other. Solving the second PDE propagates position labels along this vector field so that the second surface is tagged with a unique position on the first surface. One strength of this method is that it produces correspondences between surfaces even when they have different topologies. Even if the surfaces split apart or holes appear, the method still produces a mapping entirely automatically. We demonstrate the use of this approach to transfer texture between two surfaces that may have differing topologies.

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Point sets obtained from computer vision techniques are often noisy and non-uniform. We present a new method of surface reconstruction that can handle such data sets using anisotropic basis functions. Our reconstruction algorithm draws upon the work in variational implicit surfaces for constructing smooth and seamless 3D surfaces.Implicit functions are often formulated as a sum of weighted basis functions that are radially symmetric. Using radially symmetric basis functions inherently assumes, however, that the surface to be reconstructed is, everywhere, locally symmetric. Such an assumption is true only at planar regions, and hence, reconstruction using isotropic basis is insufficient to recover objects that exhibit sharp features. We preserve sharp features using anisotropic basis that allow the surface to vary locally. The reconstructed surface is sharper along edges and at corner points. We determine the direction of anisotropy at a point by performing principal component analysis of the data points in a small neighborhood. The resulting field of principle directions across the surface is smoothed through tensor filtering.We have applied the anisotropic basis functions to reconstruct surfaces from noisy synthetic 3D data and from real range data obtained from space carving.

No abstract

Abstract. Sensors such as video surveillance and weather monitoring systems record a significant amount of dynamic data which are represented by vector fields. We present a novel algorithm to measure the similarity of vector fields using global distributions that capture both vector field properties (e.g., vector orientation) and relational geometric information (e.g., the relative positions of two vectors in the field). We show that such global distributions are capable of distinguishing between vector fields of varying complexity and can be used to quantitatively compare similar fields.