Motion Estimation from Disparity Images

A new method for 3D rigid motion estimation from stereo is proposed in this paper. The appealing feature of this method is that it directly uses the disparity images obtained from stereo matching. We assume that the stereo rig has parallel cameras and show, in that case, the geometric and topological properties of the disparity images. Then we introduce a rigid transformation (called d-motion) that maps two disparity images of a rigidly moving object. We show how it is related to the Euclidean rigid motion and a motion estimation algorithm is derived. We show with experiments that our approach is simple and more accurate than standard approaches

Age-dependent female responses to a male ejaculate signal alter demographic opportunities for selection

A central tenet of evolutionary explanations for ageing is that the strength of selection wanes with age. However, data on age-specific expression and benefits of sexually selected traits are lacking—particularly for traits subject to sexual conflict. We addressed this by using as a model the responses of Drosophila melanogaster females of different ages to receipt of sex peptide (SP), a seminal fluid protein transferred with sperm during mating. SP can mediate sexual conflict, benefitting males while causing fitness costs in females. Virgin and mated females of all ages showed significantly reduced receptivity in response to SP. However, only young virgin females also showed increased egg laying; hence, there was a narrow demographic window of maximal responses to SP. Males gained significant ‘per mating’ fitness benefits only when mating with young females. The pattern completely reversed in matings with older females, where SP transfer was costly. The overall benefits of SP transfer (hence opportunity for selection) therefore reversed with female age. The data reveal a new example of demographic variation in the strength of selection, with convergence and conflicts of interest between males and ageing females occurring over different facets of responses to a sexually antagonistic trait

Enhancing cell therapies from the outside in: Cell surface engineering using synthetic nanomaterials

Therapeutic treatments based on the injection of living cells are in clinical use and preclinical development for diseases ranging from cancer to cardiovascular disease to diabetes. To enhance the function of therapeutic cells, a variety of chemical and materials science strategies are being developed that engineer the surface of therapeutic cells with new molecules, artificial receptors, and multifunctional nanomaterials, synthetically endowing donor cells with new properties and functions. These approaches offer a powerful complement to traditional genetic engineering strategies for enhancing the function of living cells.Massachusetts Institute of Technology. Center for Materials Science and Engineering (National Science Foundation (U.S.) DMR-0819762)United States. Dept. of Defense. Prostate Cancer Research Program (W81XWH-10-1-0290)National Institutes of Health (U.S.) (CA140476)National Institutes of Health (U.S.) (EB012352

ECONOMIC RETURNS FROM REDUCING POULTRY LITTER PHOSPHORUS WITH MICROBIAL PHYTASE

Requiring that crop applications of manure be based on phosphorus content (P-standard) could increase poultry litter disposal costs. Microbial phytase reduces litter P content and could reduce litter disposal costs under a P-standard. For a representative Virginia turkey farm, phytase costs $2,500 and could increase value of litter used for fertilizer on the turkey farm by$390 and reduce supplemental P feed costs by $1,431. Based on assumed litter demand and supply, estimated litter export prices with phytase could exceed export prices without phytase by$3.81 per ton. Phytase net returns to the farm are an estimated $ 1,435.Economic returns, Microbial phytase, Nutrient management, Phosphorus, Poultry litter, Water quality, Livestock Production/Industries,

From Pixels to Physics: Probabilistic Color De-Rendering

Consumer digital cameras use tone-mapping to produce compact, narrow-gamut images that are nonetheless visually pleasing. In doing so, they discard or distort substantial radiometric signal that could otherwise be used for computer vision. Existing methods attempt to undo these effects through deterministic maps that de-render the reported narrow-gamut colors back to their original wide-gamut sensor measurements. Deterministic approaches are unreliable, however, because the reverse narrow-to-wide mapping is one-to-many and has inherent uncertainty. Our solution is to use probabilistic maps, providing uncertainty estimates useful to many applications. We use a non-parametric Bayesian regression technique - local Gaussian process regression - to learn for each pixel's narrow-gamut color a probability distribution over the scene colors that could have created it. Using a variety of consumer cameras we show that these distributions, once learned from training data, are effective in simple probabilistic adaptations of two popular applications: multi-exposure imaging and photometric stereo. Our results on these applications are better than those of corresponding deterministic approaches, especially for saturated and out-of-gamut colors.Engineering and Applied Science

Reducing Drift in Parametric Motion Tracking

We develop a class of differential motion trackers that automatically stabilize when in finite domains. Most differ-ential trackers compute motion only relative to one previous frame, accumulating errors indefinitely. We estimate pose changes between a set of past frames, and develop a probabilistic framework for integrating those estimates. We use an approximation to the posterior distribution of pose changes as an uncertainty model for parametric motion in order to help arbitrate the use of multiple base frames. We demonstrate this framework on a simple 2D translational tracker and a 3D, 6-degree of freedom tracker

Plan-view Trajectory Estimation with Dense Stereo Background Models

In a known environment, objects may be tracked in multiple views using a set of back-ground models. Stereo-based models can be illumination-invariant, but often have undefined values which inevitably lead to foreground classification errors. We derive dense stereo models for object tracking using long-term, extended dynamic-range imagery, and by detecting and interpolating uniform but unoccluded planar regions. Foreground points are detected quickly in new images using pruned disparity search. We adopt a 'late-segmentation' strategy, using an integrated plan-view density representation. Foreground points are segmented into object regions only when a trajectory is finally estimated, using a dynamic programming-based method. Object entry and exit are optimally determined and are not restricted to special spatial zones

Face recognition with image sets using manifold density divergence

In many automatic face recognition applications, a set of a person\u27s face images is available rather than a single image. In this paper, we describe a novel method for face recognition using image sets. We propose a flexible, semi-parametric model for learning probability densities confined to highly non-linear but intrinsically low-dimensional manifolds. The model leads to a statistical formulation of the recognition problem in terms of minimizing the divergence between densities estimated on these manifolds. The proposed method is evaluated on a large data set, acquired in realistic imaging conditions with severe illumination variation. Our algorithm is shown to match the best and outperform other state-of-the-art algorithms in the literature, achieving 94% recognition rate on average

Layer-by-Layer-Assembled Multilayer Films for Transcutaneous Drug and Vaccine Delivery

We describe protein- and oligonucleotide-loaded layer-by-layer (LbL)-assembled multilayer films incorporating a hydrolytically degradable polymer for transcutaneous drug or vaccine delivery. Films were constructed based on electrostatic interactions between a cationic poly(β-amino ester) (denoted Poly-1) with a model protein antigen, ovalbumin (ova), and/or immunostimulatory CpG (cytosine−phosphate diester−guanine-rich) DNA oligonucleotide adjuvant molecules. Linear growth of nanoscale Poly-1/ova bilayers was observed. Dried ova protein-loaded films rapidly deconstructed when rehydrated in saline solutions, releasing ova as nonaggregated/nondegraded protein, suggesting that the structure of biomolecules integrated into these multilayer films is preserved during release. Using confocal fluorescence microscopy and an in vivo murine ear skin model, we demonstrated delivery of ova from LbL films into barrier-disrupted skin, uptake of the protein by skin-resident antigen-presenting cells (Langerhans cells), and transport of the antigen to the skin-draining lymph nodes. Dual incorporation of ova and CpG oligonucleotides into the nanolayers of LbL films enabled dual release of the antigen and adjuvant with distinct kinetics for each component; ova was rapidly released, while CpG was released in a relatively sustained manner. Applied as skin patches, these films delivered ova and CpG to Langerhans cells in the skin. To our knowledge, this is the first demonstration of LbL films applied for the delivery of biomolecules into skin. This approach provides a new route for storage of vaccines and other immunotherapeutics in a solid-state thin film for subsequent delivery into the immunologically rich milieu of the skin.Massachusetts Institute of Technology. Institute for Soldier NanotechnologiesSingapore. Agency for Science, Technology and Researc