We describe an image based rendering approach that generalizes many image based rendering algorithms currently in use including light field rendering and view-dependent texture mapping. In particular it allows for lumigraph style rendering from a set of input cameras that are not restricted to a plane or to any specific manifold. In the case of regular and planar input camera positions, our algorithm reduces to a typical lumigraph approach. In the case of fewer cameras and good approximate geometry, our algorithm behaves like view-dependent texture mapping. Our algorithm achieves this flexibility because it is designed to meet a set of desirable goals that we describe. We demonstrate this flexibility with a variety of examples.

Here we provide the first genome-wide, high-resolution map of the phylogenetic origin of the genome of most extant laboratory mouse inbred strains. Our analysis is based on the genotypes of wild caught mice from three subspecies of Mus musculus. We demonstrate that classical laboratory strains are derived from a few fancy mice with limited haplotype diversity. Their genomes are overwhelmingly M. m. domesticus in origin and the remainder is mostly of Japanese origin. We generated genome-wide haplotype maps based on identity by descent from fancy mice and demonstrate that classical inbred strains have limited and non-randomly distributed genetic diversity. In contrast, wild-derived laboratory strains represent a broad sampling of diversity within M. musculus. Intersubspecific introgression is pervasive in these strains and contamination by laboratory stocks has played role in this process. The subspecific origin, haplotype diversity and identity by descent maps can be visualized and searched online.

I present a data-driven model for isotropic bidirectional reflectance distribution functions (BRDFs) based on acquired reflectance data. Instead of using analytic reflectance models, each BRDF is represented as a dense set of measurements. This representation allows interpolation and extrapolation in the space of acquired BRDFs to create new BRDFs. Each acquired BRDF is treated as a single high-dimensional vector taken from the space of all possible BRDFs. Both linear (subspace) and non-linear (manifold) dimensionality reduction tools are applied in an effort to discover a lower-dimensional representation that characterizes the acquired BRDFs. To complete the model, users are provided with the means for defining perceptually meaningful parametrizations that allow them to navigate in the reduced-dimension BRDF space. On the low-dimensional manifold, movement along these directions produces novel, but valid, BRDFs.By analyzing a large collection of reflectance data, I also derive two novel reflectance sampling procedures that require fewer total measurements than standard uniform sampling approaches. Using densely sampled measurements the general surface reflectance function is analyzed to determine the local signal variation at each point in the function's domain. Wavelet analysis is used to derive a common basis for all of the acquired reflectance functions, as well as a non-uniform sampling pattern that corresponds to all non-zero wavelet coefficients. Second, I show that the reflectance of an arbitrary material can be represented as a linear combination of the surface reflectance functions. Furthermore, this analysis specifies a reduced set of sampling points that permits the robust estimation of the coefficients of this linear combination. These procedures dramatically shorten the acquisition time for isotropic reflectance measurements. I would like to thank Matt Brand for advising me on many parts of the project. Technical discussions with Matt, his algorithms, and his research code were essential in developing this data-driven reflectance model.

The JAX Diversity Outbred population is a new mouse resource derived from partially inbred Collaborative Cross strains and maintained by randomized outcrossing. As such, it segregates the same allelic variants as the Collaborative Cross but embeds these in a distinct population architecture in which each animal has a high degree of heterozygosity and carries a unique combination of alleles. Phenotypic diversity is striking and often divergent from phenotypes seen in the founder strains of the Collaborative Cross. Allele frequencies and recombination density in early generations of Diversity Outbred mice are consistent with expectations based on simulations of the mating design. We describe analytical methods for genetic mapping using this resource and demonstrate the power and high mapping resolution achieved with this population by mapping a serum cholesterol trait to a 2-Mb region on chromosome 3 containing only 11 genes. Analysis of the estimated allele effects in conjunction with complete genome sequence data of the founder strains reduced the pool of candidate polymorphisms to seven SNPs, five of which are located in an intergenic region upstream of the Foxo1 gene.

In this paper, we describe an efficient image-based approach to computing and shading visual hulls from silhouette image data. Our algorithm takes advantage of epipolar geometry and incremental computation to achieve a constant rendering cost per rendered pixel. It does not suffer from the computation complexity, limited resolution, or quantization artifacts of previous volumetric approaches. We demonstrate the use of this algorithm in a real-time virtualized reality application running off a small number of video streams.

The Collaborative Cross (CC) is a mouse recombinant inbred strain panel that is being developed as a resource for mammalian systems genetics. Here we describe an experiment that uses partially inbred CC lines to evaluate the genetic properties and utility of this emerging resource. Genome-wide analysis of the incipient strains reveals high genetic diversity, balanced allele frequencies, and dense, evenly distributed recombination sites-all ideal qualities for a systems genetics resource. We map discrete, complex, and biomolecular traits and contrast two quantitative trait locus (QTL) mapping approaches. Analysis based on inferred haplotypes improves power, reduces false discovery, and provides information to identify and prioritize candidate genes that is unique to multifounder crosses like the CC. The number of expression QTLs discovered here exceeds all previous efforts at eQTL mapping in mice, and we map local eQTL at 1-Mb resolution. We demonstrate that the genetic diversity of the CC, which derives from random mixing of eight founder strains, results in high phenotypic diversity and enhances our ability to map causative loci underlying complex disease-related traits.

An exciting new area in computer graphics is the synthesis of novel images with photographic effect from an initial database of reference images. This is the primary theme of imagebased rendering algorithms. This research extends the light field and lumigraph image-based rendering methods and greatly extends their utility, especially in scenes with much depth variation. First, we have added the ability to vary the apparent focus within a light field using intuitive camera-like controls such as a variable aperture and focus ring. As with lumigraphs, we allow for more general and flexible focal surfaces than a typical focal plane.However, this parameterization works independently of scene geometry; we do not need to recover actual or approximate geometry of the scene for focusing. In addition, we present a method for using multiple focal surfaces in a single image rendering process.

The Collaborative Cross Consortium reports here on the development of a unique genetic resource population. The Collaborative Cross (CC) is a multiparental recombinant inbred panel derived from eight laboratory mouse inbred strains. Breeding of the CC lines was initiated at multiple international sites using mice from The Jackson Laboratory. Currently, this innovative project is breeding independent CC lines at the University of North Carolina (UNC), at Tel Aviv University (TAU), and at Geniad in Western Australia (GND). These institutions aim to make publicly available the completed CC lines and their genotypes and sequence information. We genotyped, and report here, results from 458 extant lines from UNC, TAU, and GND using a custom genotyping array with 7500 SNPs designed to be maximally informative in the CC and used a novel algorithm to infer inherited haplotypes directly from hybridization intensity patterns. We identified lines with breeding errors and cousin lines generated by splitting incipient lines into two or more cousin lines at early generations of inbreeding. We then characterized the genome architecture of 350 genetically independent CC lines. Results showed that founder haplotypes are inherited at the expected frequency, although we also consistently observed highly significant transmission ratio distortion at specific loci across all three populations. On chromosome 2, there is significant overrepresentation of WSB/EiJ alleles, and on chromosome X, there is a large deficit of CC lines with CAST/EiJ alleles. Linkage disequilibrium decays as expected and we saw no evidence of gametic disequilibrium in the CC population as a whole or in random subsets of the population. Gametic equilibrium in the CC population is in marked contrast to the gametic disequilibrium present in a large panel of classical inbred strains. Finally, we discuss access to the CC population and to the associated raw data describing the genetic structure of individual lines. Integration of rich phenotypic and genomic data over time and across a wide variety of fields will be vital to delivering on one of the key attributes of the CC, a common genetic reference platform for identifying causative variants and genetic networks determining traits in mammals.