Contour Generator Points for Threshold Selection and a Novel Photo-Consistency Measure for Space Carving

Space carving has emerged as a powerful method for multiview scene reconstruction. Although a wide variety of methods have been proposed, the quality of the reconstruction remains highly-dependent on the photometric consistency measure, and the threshold used to carve away voxels. In this paper, we present a novel photo-consistency measure that is motivated by a multiset variant of the chamfer distance. The new measure is robust to high amounts of within-view color variance and also takes into account the projection angles of back-projected pixels. Another critical issue in space carving is the selection of the photo-consistency threshold used to determine what surface voxels are kept or carved away. In this paper, a reliable threshold selection technique is proposed that examines the photo-consistency values at contour generator points. Contour generators are points that lie on both the surface of the object and the visual hull. To determine the threshold, a percentile ranking of the photo-consistency values of these generator points is used. This improved technique is applicable to a wide variety of photo-consistency measures, including the new measure presented in this paper. Also presented in this paper is a method to choose between photo-consistency measures, and voxel array resolutions prior to carving using receiver operating characteristic (ROC) curves.

Periodic Motion Detection and Estimation via Space-Time Sampling

A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

Search Space Reduction in QoS Routing

To provide real-time service or engineer constrained-based paths, networks require the underlying routing algorithm to be able to find low-cost paths that satisfy given Quality-of-Service (QoS) constraints. However, the problem of constrained shortest (least-cost) path routing is known to be NP-hard, and some heuristics have been proposed to find a near-optimal solution. However, these heuristics either impose relationships among the link metrics to reduce the complexity of the problem which may limit the general applicability of the heuristic, or are too costly in terms of execution time to be applicable to large networks. In this paper, we focus on solving the delay-constrained minimum-cost path problem, and present a fast algorithm to find a near-optimal solution. This algorithm, called DCCR (for Delay-Cost-Constrained Routing), is a variant of the k-shortest path algorithm. DCCR uses a new adaptive path weight function together with an additional constraint imposed on the path cost, to restrict the search space. Thus, DCCR can return a near-optimal solution in a very short time. Furthermore, we use the method proposed by Blokh and Gutin to further reduce the search space by using a tighter bound on path cost. This makes our algorithm more accurate and even faster. We call this improved algorithm SSR+DCCR (for Search Space Reduction+DCCR). Through extensive simulations, we confirm that SSR+DCCR performs very well compared to the optimal but very expensive solution.

Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions

A learning based framework is proposed for estimating human body pose from a single image. Given a differentiable function that maps from pose space to image feature space, the goal is to invert the process: estimate the pose given only image features. The inversion is an ill-posed problem as the inverse mapping is a one to many process. Hence multiple solutions exist, and it is desirable to restrict the solution space to a smaller subset of feasible solutions. For example, not all human body poses are feasible due to anthropometric constraints. Since the space of feasible solutions may not admit a closed form description, the proposed framework seeks to exploit machine learning techniques to learn an approximation that is smoothly parameterized over such a space. One such technique is Gaussian Process Latent Variable Modelling. Scaled conjugate gradient is then used find the best matching pose in the space of feasible solutions when given an input image. The formulation allows easy incorporation of various constraints, e.g. temporal consistency and anthropometric constraints. The performance of the proposed approach is evaluated in the task of upper-body pose estimation from silhouettes and compared with the Specialized Mapping Architecture. The estimation accuracy of the Specialized Mapping Architecture is at least one standard deviation worse than the proposed approach in the experiments with synthetic data. In experiments with real video of humans performing gestures, the proposed approach produces qualitatively better estimation results.

Tracking Human Body Pose on a Learned Smooth Space

Particle filtering is a popular method used in systems for tracking human body pose in video. One key difficulty in using particle filtering is caused by the curse of dimensionality: generally a very large number of particles is required to adequately approximate the underlying pose distribution in a high-dimensional state space. Although the number of degrees of freedom in the human body is quite large, in reality, the subset of allowable configurations in state space is generally restricted by human biomechanics, and the trajectories in this allowable subspace tend to be smooth. Therefore, a framework is proposed to learn a low-dimensional representation of the high-dimensional human poses state space. This mapping can be learned using a Gaussian Process Latent Variable Model (GPLVM) framework. One important advantage of the GPLVM framework is that both the mapping to, and mapping from the embedded space are smooth; this facilitates sampling in the low-dimensional space, and samples generated in the low-dimensional embedded space are easily mapped back into the original highdimensional space. Moreover, human body poses that are similar in the original space tend to be mapped close to each other in the embedded space; this property can be exploited when sampling in the embedded space. The proposed framework is tested in tracking 2D human body pose using a Scaled Prismatic Model. Experiments on real life video sequences demonstrate the strength of the approach. In comparison with the Multiple Hypothesis Tracking and the standard Condensation algorithm, the proposed algorithm is able to maintain tracking reliably throughout the long test sequences. It also handles singularity and self occlusion robustly.

Hippocampal Modulation of Recognition, Conditioning, Timing, and Space: Why So Many Functions?

Advanced Research Projects Agency (ONR N00014-92-J-4015); National Science Foundation (IRI-90-24877); Office of Naval Research (N00014-91-J-1309)

Space, Time and Learning in the Hippocampus: How Fine Spatial and Temporal Scales Are Expanded into Population Codes for Behavioral Control

The hippocampus participates in multiple functions, including spatial navigation, adaptive timing, and declarative (notably, episodic) memory. How does it carry out these particular functions? The present article proposes that hippocampal spatial and temporal processing are carried out by parallel circuits within entorhinal cortex, dentate gyrus, and CA3 that are variations of the same circuit design. In particular, interactions between these brain regions transform fine spatial and temporal scales into population codes that are capable of representing the much larger spatial and temporal scales that are needed to control adaptive behaviors. Previous models of adaptively timed learning propose how a spectrum of cells tuned to brief but different delays are combined and modulated by learning to create a population code for controlling goal-oriented behaviors that span hundreds of milliseconds or even seconds. Here it is proposed how projections from entorhinal grid cells can undergo a similar learning process to create hippocampal place cells that can cover a space of many meters that are needed to control navigational behaviors. The suggested homology between spatial and temporal processing may clarify how spatial and temporal information may be integrated into an episodic memory.

Monasticism and its limits: rematerialising monastic space in early medieval Ireland

This thesis creates a multi-faceted archaeological context for early Irish monasticism, so as to ‘rematerialise’ a phenomenon that has been neglected by recent archaeological scholarship. Following revision of earlier models of the early Irish Church, archaeologists are now faced with redefining monasticism and distinguishing it from other diverse forms of Christian lifestyle. This research addresses this challenge, exploring the ways in which material limits can be set on the monastic phenomenon. The evidence for early Irish monasticism does not always conform to modern expectations of its character, and monastic space must be examined as culturally unique in its own right - though this thesis demonstrates that early Irish monasticism was by no means as unorthodox in its contemporary European setting as has previously been suggested. The research is informed by theories of the body, habitus and space, drawing on a wide body of archaeological, religious, sociological and anthropological thought. The data-set comprises evidences gathered through field-survey, reassessment of archaeological scholarship, historical research and cartographic research, enabling consideration of the ways in which early Irish monastics engaged with their environments. A sample of thirty-one early Irish ecclesiastical sites plus Iona forms the basis for discussion of the location and layout of monastic space, the ways in which monastics used buildings and space in their daily lives, the relationship of monasticism and material culture, the setting of mental and physical limits on monastic space and monastic bodies, and the variety of monastic lifestyles that pertained in early medieval Ireland. The study then examines the Christian landscapes of two case-studies in mid-Western Ireland in order to illustrate how monasticism functioned on the ground in these areas. As this research shows, the material complexities of early Irish monastic life are capable of archaeological definition in terms of both communal and personal lived experience.

Preserving patent policy space and securing access to medicines in developing countries: the role of states and pharmaceutical corporations

This thesis examines the tension between patent rights and the right to health and it recognizes patent rights on pharmaceutical products as one of the factors responsible for the problem of lack of access to affordable medicines in developing countries. The thesis contends that, in order to preserve their patent policy space and secure access to affordable medicines for their citizens, developing countries should incorporate a model of human rights into the design, implementation, interpretation, and enforcement of their national patent laws. The thesis provides a systematic analysis of court decisions from four key developing countries (Brazil, India, Kenya, and South Africa) and it assesses how the national courts in these countries resolve the tension between patent rights and the right to health. Essentially, this thesis demonstrates how a model of human rights can be incorporated into the adjudication of disputes involving patent rights in national courts. Focusing specifically on Brazil, the thesis equally demonstrates how policy makers and law makers at the national level can incorporate a model of human rights into the design or amendment of their national patent law. This thesis also contributes to the ongoing debate in the field of business and human rights with regard to the mechanisms that can be used to hold corporate actors accountable for their human rights responsibilities. This thesis recognizes that, while states bear the primary responsibility to respect, protect, and fulfil the right to health, corporate actors such as pharmaceutical companies also have a baseline responsibility to respect the right to health. This thesis therefore contends that pharmaceutical companies that own patent rights on pharmaceutical products can be held accountable for their right to health responsibilities at the national level through the incorporation of a model of civic participation into a country’s patent law system.

Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

Progress in intra-articular therapy.

Diarthrodial joints are well suited to intra-articular injection, and the local delivery of therapeutics in this fashion brings several potential advantages to the treatment of a wide range of arthropathies. Possible benefits over systemic delivery include increased bioavailability, reduced systemic exposure, fewer adverse events, and lower total drug costs. Nevertheless, intra-articular therapy is challenging because of the rapid egress of injected materials from the joint space; this elimination is true of both small molecules, which exit via synovial capillaries, and of macromolecules, which are cleared by the lymphatic system. In general, soluble materials have an intra-articular dwell time measured only in hours. Corticosteroids and hyaluronate preparations constitute the mainstay of FDA-approved intra-articular therapeutics. Recombinant proteins, autologous blood products and analgesics have also found clinical use via intra-articular delivery. Several alternative approaches, such as local delivery of cell and gene therapy, as well as the use of microparticles, liposomes, and modified drugs, are in various stages of preclinical development.

Different stimuli, different spatial codes: a visual map and an auditory rate code for oculomotor space in the primate superior colliculus.

Maps are a mainstay of visual, somatosensory, and motor coding in many species. However, auditory maps of space have not been reported in the primate brain. Instead, recent studies have suggested that sound location may be encoded via broadly responsive neurons whose firing rates vary roughly proportionately with sound azimuth. Within frontal space, maps and such rate codes involve different response patterns at the level of individual neurons. Maps consist of neurons exhibiting circumscribed receptive fields, whereas rate codes involve open-ended response patterns that peak in the periphery. This coding format discrepancy therefore poses a potential problem for brain regions responsible for representing both visual and auditory information. Here, we investigated the coding of auditory space in the primate superior colliculus(SC), a structure known to contain visual and oculomotor maps for guiding saccades. We report that, for visual stimuli, neurons showed circumscribed receptive fields consistent with a map, but for auditory stimuli, they had open-ended response patterns consistent with a rate or level-of-activity code for location. The discrepant response patterns were not segregated into different neural populations but occurred in the same neurons. We show that a read-out algorithm in which the site and level of SC activity both contribute to the computation of stimulus location is successful at evaluating the discrepant visual and auditory codes, and can account for subtle but systematic differences in the accuracy of auditory compared to visual saccades. This suggests that a given population of neurons can use different codes to support appropriate multimodal behavior.

Measurements of Epidural Space Depth Using Preexisting CT Scans Correlate with Loss of Resistance Depth during Thoracic Epidural Catheter Placement.

Background. Thoracic epidural catheters provide the best quality postoperative pain relief for major abdominal and thoracic surgical procedures, but placement is one of the most challenging procedures in the repertoire of an anesthesiologist. Most patients presenting for a procedure that would benefit from a thoracic epidural catheter have already had high resolution imaging that may be useful to assist placement of a catheter. Methods. This retrospective study used data from 168 patients to examine the association and predictive power of epidural-skin distance (ESD) on computed tomography (CT) to determine loss of resistance depth acquired during epidural placement. Additionally, the ability of anesthesiologists to measure this distance was compared to a radiologist, who specializes in spine imaging. Results. There was a strong association between CT measurement and loss of resistance depth (P < 0.0001); the presence of morbid obesity (BMI > 35) changed this relationship (P = 0.007). The ability of anesthesiologists to make CT measurements was similar to a gold standard radiologist (all individual ICCs > 0.9). Conclusions. Overall, this study supports the examination of a recent CT scan to aid in the placement of a thoracic epidural catheter. Making use of these scans may lead to faster epidural placements, fewer accidental dural punctures, and better epidural blockade.

When the library is located in prime real estate: a case study on the loss of space from the Duke University Medical Center Library and Archives.

The Duke University Medical Center Library and Archives is located in the heart of the Duke Medicine campus, surrounded by Duke Hospital, ambulatory clinics, and numerous research facilities. Its location is considered prime real estate, given its adjacency to patient care, research, and educational activities. In 2005, the Duke University Library Space Planning Committee had recommended creating a learning center in the library that would support a variety of educational activities. However, the health system needed to convert the library's top floor into office space to make way for expansion of the hospital and cancer center. The library had only five months to plan the storage and consolidation of its journal and book collections, while working with the facilities design office and architect on the replacement of key user spaces on the top floor. Library staff worked together to develop plans for storing, weeding, and consolidating the collections and provided input into renovation plans for users spaces on its mezzanine level. The library lost 15,238 square feet (29%) of its net assignable square footage and a total of 16,897 (30%) gross square feet. This included 50% of the total space allotted to collections and over 15% of user spaces. The top-floor space now houses offices for Duke Medicine oncology faculty and staff. By storing a large portion of its collection off-site, the library was able to remove more stacks on the remaining stack level and convert them to user spaces, a long-term goal for the library. Additional space on the mezzanine level had to be converted to replace lost study and conference room spaces. While this project did not match the recommended space plans for the library, it underscored the need for the library to think creatively about the future of its facility and to work toward a more cohesive master plan.