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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