Analysis of Two-Dimensional Non-Rigid Shapes

Analysis of deformable two-dimensional shapes is an important problem, encountered in numerous pattern recognition, computer vision and computer graphics applications. In this paper, we address three major problems in the analysis of non-rigid shapes: similarity, partial similarity, and correspondence. We present an axiomatic construction of similarity criteria for deformation-invariant shape comparison, based on intrinsic geometric properties of the shapes, and show that such criteria are related to the Gromov-Hausdorff distance. Next, we extend the problem of similarity computation to shapes which have similar parts but are dissimilar when considered as a whole, and present a construction of set-valued distances, based on the notion of Pareto optimality. Finally, we show that the correspondence between non-rigid shapes can be obtained as a byproduct of the non-rigid similarity problem. As a numerical framework, we use the generalized multidimensional scaling (GMDS) method, which is the numerical core of the three problems addressed in this paper.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.     

Parallel evolution using multi-chromosome cartesian genetic programming

Parallel and distributed methods for evolutionary algorithms have concentrated on maintaining multiple populations of genotypes, where each genotype in a population encodes a potential solution to the problem. In this paper, we investigate the parallelisation of the genotype itself into a collection of independent chromosomes which can be evaluated in parallel. We call this multi-chromosomal evolution (MCE). We test this approach using Cartesian Genetic Programming and apply MCE to a series of digital circuit design problems to compare the efficacy of MCE with a conventional single chromosome approach (SCE). MCE can be readily used for many digital circuits because they have multiple outputs. In MCE, an independent chromosome is assigned to each output. When we compare MCE with SCE we find that MCE allows us to evolve solutions much faster. In addition, in some cases we were able to evolve solutions with MCE that we unable to with SCE. In a case-study, we investigate how MCE can be applied to to a single objective problem in the domain of image classification, namely, the classification of breast X-rays for cancer. To apply MCE to this problem, we identify regions of interest (RoI) from the mammograms, divide the RoI into a collection of sub-images and use a chromosome to classify each sub-image. This problem allows us to evaluate various evolutionary mutation operators which can pairwise swap chromosomes either randomly or topographically or reuse chromosomes in place of other chromosomes.     

Building brains for bodies

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We are building an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to think by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.     

Edge detection and characterization of digitized images

Pattern Analysis and Applications - We present a method for determining which of a large set of pixels are inside or on the boundary of a polygon. The method works much quicker than the standard...     

Threshold for Millimeter-Wave (60 GHz)-Induced Ocular Injury

Journal of Infrared, Millimeter, and Terahertz Waves - Millimeter waves (MMW) absorbed by skin or cornea may induce damage by heat. We have developed a 60 GHz MMW exposure-induced eye...     

Photoacoustic‐Guided Surgery with Indocyanine Green‐Coated Superparamagnetic Iron Oxide Nanoparticle Clusters

A common cause of local tumor recurrence in brain tumor surgery results from incomplete surgical resection. Adjunctive technologies meant to facilitate gross total resection have had limited efficacy to date. Contrast agents used to delineate tumors preoperatively cannot be easily or accurately used in the real‐time operative setting. Although multimodal imaging contrast agents are developed to help the surgeon discern tumor from normal tissue in the operating room, these contrast agents are not readily translatable. This study has developed a novel contrast agent comprised solely of two Food and Drug Administration approved components, indocyanine green (ICG) and superparamagnetic iron oxide (SPIO) nanoparticles—with no additional amphiphiles or carrier materials, to enable preoperative detection by magnetic resonance (MR) imaging and intraoperative photoacoustic (PA) imaging. The encapsulation efficiency of both ICG and SPIO within the formulated clusters is ≈100%, and the total ICG payload is 20–30% of the total weight (ICG + SPIO). The ICG–SPIO clusters are stable in physiologic conditions; can be taken up within tumors by enhanced permeability and retention; and are detectable by MR. In a preclinical surgical resection model in mice, following injection of ICG–SPIO clusters, animals undergoing PA‐guided surgery demonstrate increased progression‐free survival compared to animals undergoing microscopic surgery.     

The "Heart Area" of Juan Canalejo Hospital Complex. A new approach to clinical management

The present work describes the process by which the pilot project of clinical management of the Hospital Complex Juan Canalejo, designated as "Heart Area", was implemented. In the first section, the needs and reasons that led to the undertaking of this project are explained. The project's objectives and operative strategies are listed. In the Material and Methods section, three basic aspects of the "Heart Area" are described: selection criteria of the "Area", its structure and function, and its foundation and development. In the Results section, we compare the activity undertaken in the "Area" to the situation present prior to its implementation, in relation to quality and costs. Finally, in the Conclusions, we comment on the important implications that our project can have within the Hospital Complex Juan Canalejo as well as in the health care field in general.     

Neural mechanisms for synthesizing sensory information and producing adaptive behaviors

The ability to integrate information from different sensory systems is a fundamental characteristic of the brain. Because different bits of information are derived from different sensory channels, their synthesis markedly enhances the detection and identification of external stimuli. The neural substrate for such "multisensory" integration is provided by neurons that receive convergent input from two or more sensory modalities. Many such multisensory neurons are found in the superior colliculus (SC), a midbrain structure that plays a significant role in overt attentive and orientation behaviors. The various principles governing the integration of visual, auditory, and somatosensory inputs in SC neurons have been explored in several species. Thus far, the evidence suggests a remarkable conservation of integrative features during vertebrate evolution. One of the most robust of these principles is based on spatial relationships: a striking enhancement in activity is induced in a multisensory neuron when two different sensory stimuli (e.g., visual and auditory) are in spatial concordance, whereas a profound response depression can be induced when these cues are spatially discordant. The most extensive physiological observations have been made in cat, and in this species the same principles that have been shown to govern multisensory integration at the level of the individual SC neuron have also been shown to govern overt attentive and orientation responses to multisensory stimuli. Most surprising, however, is the critical role played by association (i.e. anterior ectosylvian) cortex in facilitating these midbrain processes. In the absence of the modulating corticotectal influences, multisensory SC neurons in cat are unable to integrate the different sensory cues converging upon them in an adult-like fashion, and are unable to mediate overt multisensory behaviors. This situation appears quite similar to that observed during early postnatal life. When multisensory SC neurons first appear, they are able to respond to multiple sensory inputs but are unable to synthesize these inputs to significantly enhance or degrade their responses. During ontogeny, individual multisensory neurons develop this capacity abruptly, but at very different ages, until the mature population condition is reached after several postnatal months. It appears likely that the abrupt onset of this capacity in any individual SC neuron reflects the maturation of inputs from anterior ectosylvian cortex. Presumably, the functional coupling of cortex with an individual SC neuron is essential to initiate and maintain that neuron's capability for multisensory integration throughout its life.     

Intrinsic plagiarism analysis

Research in automatic text plagiarism detection focuses on algorithms that compare suspicious documents against a collection of reference documents. Recent approaches perform well in identifying copied or modified foreign sections, but they assume a closed world where a reference collection is given. This article investigates the question whether plagiarism can be detected by a computer program if no reference can be provided, e.g., if the foreign sections stem from a book that is not available in digital form. We call this problem class intrinsic plagiarism analysis; it is closely related to the problem of authorship verification. Our contributions are threefold. (1) We organize the algorithmic building blocks for intrinsic plagiarism analysis and authorship verification and survey the state of the art. (2) We show how the meta learning approach of Koppel and Schler, termed “unmasking”, can be employed to post-process unreliable stylometric analysis results. (3) We operationalize and evaluate an analysis chain that combines document chunking, style model computation, one-class classification, and meta learning.