TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture,Layout, and Context

This paper details a new approach for learning a discriminative model of object classes, incorporating texture, layout, and context information efficiently. The learned model is used for automatic visual understanding and semantic segmentation of photographs. Our discriminative model exploits texture-layout filters, novel features based on textons, which jointly model patterns of texture and their spatial layout. Unary classification and feature selection is achieved using shared boosting to give an efficient classifier which can be applied to a large number of classes. Accurate image segmentation is achieved by incorporating the unary classifier in a conditional random field, which (i) captures the spatial interactions between class labels of neighboring pixels, and (ii) improves the segmentation of specific object instances. Efficient training of the model on large datasets is achieved by exploiting both random feature selection and piecewise training methods. High classification and segmentation accuracy is demonstrated on four varied databases: (i) the MSRC 21-class database containing photographs of real objects viewed under general lighting conditions, poses and viewpoints, (ii) the 7-class Corel subset and (iii) the 7-class Sowerby database used in He et al. (Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 695–702, June 2004), and (iv) a set of video sequences of television shows. The proposed algorithm gives competitive and visually pleasing results for objects that are highly textured (grass, trees, etc.), highly structured (cars, faces, bicycles, airplanes, etc.), and even articulated (body, cow, etc.). J. Shotton is now working at Toshiba Corporate Research & Development Center, Kawasaki, Japan.     

Guaranteeing hard real-time traffic with legitimately short deadlines with the timed token protocol

Synchronous bandwidth, defined as the maximum time a node is allowed to send its synchronous messages while holding the token, is a sensitive parameter for deadline guarantees of synchronous messages in any timed token network. In order to offer such guarantees, synchronous bandwidth has to be allocated carefully to each individual node. This paper studies the synchronous bandwidth allocated to those synchronous message streams whose deadlines are less than twice the Target Token Rotation Time (TTRT). A new approach for allocating synchronous bandwidth to such streams, which can be used with any previously published local synchronous bandwidth allocation (SBA) for guaranteeing a general synchronous message set with its minimum deadline (D_min) no less than 2 · TTRT, is proposed. The proposed scheme can be applied efficiently in practice to any general synchronous message set with D_min > TTRT. Numerical examples are presented to demonstrate the enhanced performance of this new local scheme over any of the previously published local SBA schemes.     

A priori and a posteriori analysis for a locking-free low order quadrilateral hybrid finite element for Reissner–Mindlin plates

This paper proposes a quadrilateral finite element method of the lowest order for Reissner–Mindlin (R–M) plates on the basis of Hellinger–Reissner variational principle, which includes variables of displacements, shear stresses and bending moments. This method uses continuous piecewise isoparametric bilinear interpolation for the approximation of transverse displacement and rotation. The piecewise-independent shear stress/bending moment approximation is constructed by following a self-equilibrium criterion and a shear-stress-enhanced condition. A priori and reliable a posteriori error estimates are derived and shown to be uniform with respect to the plate thickness t. Numerical experiments confirm the theoretical results.     

Detection of colorectal adenoma and cancer based on transthyretin and C3a-desArg serum levels

Colorectal cancer is the second leading cause of cancer death, and it develops from benign colorectal adenomas in over 95% of patients. Early detection of these cancer precursors by screening tests and their removal can potentially eradicate more than 95% of colorectal cancers before they develop. To discover sensitive and specific biomarkers for improvement of pre‐clinical diagnosis of colorectal adenoma and cancer, we analysed in two independent studies (n = 87 and n = 83 patients) serum samples from colorectal cancer (stage III), colorectal adenoma and control patients using SELDI‐TOF‐MS. Extensive statistical analysis was performed to establish homogeneous patient groups based on their clinical data. Two biomarkers that were each able to distinguish control patients from either colorectal adenoma or colorectal cancer patients (p<0.001) were identified as transthyretin (pre‐albumin) and C3a‐desArg by MS/MS and were further validated by antibody‐based assays (radial immunodiffusion, ELISA). A combination of both proteins clearly indicated the presence of colorectal adenoma or carcinoma. Using a cut‐off of <0.225 g/L for transthyretin and >1974 ng/mL for C3a‐desArg, we found a sensitivity and specificity for colorectal adenoma of 96% and 70%, respectively.     

Probabilistic fusion of stereo with color and contrast for bilayer segmentation

This paper describes models and algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from color/contrast or from stereo alone is known to be error-prone. Here, color, contrast, and stereo matching information are fused to infer layers accurately and efficiently. The first algorithm, layered dynamic programming (LDP), solves stereo in an extended six-state space that represents both foreground/background layers and occluded regions. The stereo-match likelihood is then fused with a contrast-sensitive color model that is learned on-the-fly and stereo disparities are obtained by dynamic programming. The second algorithm, layered graph cut (LGC), does not directly solve stereo. Instead, the stereo match likelihood is marginalized over disparities to evaluate foreground and background hypotheses and then fused with a contrast-sensitive color model like the one used in LDP. Segmentation is solved efficiently by ternary graph cut. Both algorithms are evaluated with respect to ground truth data and found to have similar performance, substantially better than either stereo or color/contrast alone. However, their characteristics with respect to computational efficiency are rather different. The algorithms are demonstrated in the application of background substitution and shown to give good quality composite video output.     

Electrokinetic microslit experiments to analyse the charge formation at solid/liquid interfaces

Electrokinetic effects play an important role in microfluidics and nanofluidics. Although the related phenomena are often utilized to control fluid flow and sample transport in lab-on-a-chip devices, their dependency on the surface charges on the channel walls often remain enigmatic. This is mainly due to the lack of adequate experimental methods to analyse the electrical charging of solid/liquid interfaces of interest. To address this need, an experimental set-up—designated as microslit electrokinetic set-up (MES)—has been recently developed and applied for the investigation of charge formation processes at planar solid/liquid interfaces. The device permits to perform streaming potential and streaming current measurements across a rectangular streaming channel formed by two parallel sample carriers (20×10×3 mm³) at variable distance allowing for the determination of the surface conductivity. Utilizing the MES, charge characteristics can be determined for a wide variety of materials prepared as thin films on top of planar glass substrates. Streaming potential and streaming current data permit to investigate the mechanisms of charge formation while surface conductivity data provide information about mobile charge carriers located in different zones at the interface. The applicability of this advanced experimental approach is demonstrated with examples obtained for surfaces with different levels of complexity:

1. Preferential ion adsorption onto unpolar fluoropolymer (Teflon^® AF) films was characterized in simple electrolyte solutions; the results were quantitatively evaluated with respect to interfacial ion concentrations.
2. Interrelation of charge density and conformation of grafted poly(L-glutamic acid layers) were unravelled from the determination of pH-depended variations of surface conductivity and layer thickness.
3. The impact of spatial confinements of surface functional groups on their acid–base behaviour was studied with self-assembled monomolecular films of alkanethiols chemisorbed on gold.
4. Charging of and ion mobility within poly(acrylic acid) (PAA) brushes prepared by a Langmuir–Blodgett technique were analysed at varied pH and ionic strength.
5. Interfacial modes of adsorbed proteins were distinguished at two polymer surfaces with varied hydrophobicity/charge density.

     

Runtime analysis of the (mu+1) EA on simple Pseudo-Boolean functions

Although Evolutionary Algorithms (EAs) have been successfully applied to optimization in discrete search spaces, theoretical developments remain weak, in particular for population-based EAs. This paper presents a first rigorous analysis of the (mu+1) EA on pseudo-Boolean functions. Using three well-known example functions from the analysis of the (1+1) EA, we derive bounds on the expected runtime and success probability. For two of these functions, upper and lower bounds on the expected runtime are tight, and on all three functions, the (mu+1) EA is never more efficient than the (1+1) EA. Moreover, all lower bounds grow with mu. On a more complicated function, however, a small increase of mu probably decreases the expected runtime drastically.This paper develops a new proof technique that bounds the runtime of the (mu+1) EA. It investigates the stochastic process for creating family trees of individuals; the depth of these trees is bounded. Thereby, the progress of the population towards the optimum is captured. This new technique is general enough to be applied to other population-based EAs.     

A symbolic summation approach to Feynman integral calculus

Given a Feynman parameter integral, depending on a single discrete variable N$N$ and a real parameter ε$\epsilon$, we discuss a new algorithmic framework to compute the first coefficients of its Laurent series expansion in ε$\epsilon$. In a first step, the integrals are expressed by hypergeometric multi-sums by means of symbolic transformations. Given this sum format, we develop new summation tools to extract the first coefficients of its series expansion whenever they are expressible in terms of indefinite nested product–sum expressions. In particular, we enhance the known multi-sum algorithms to derive recurrences for sums with complicated boundary conditions, and we present new algorithms to find formal Laurent series solutions of a given recurrence relation.     

Progressive Virtual Beam Lights

A recent technique that forms virtual ray lights (VRLs) from path segments in media, reduces the artifacts common to VPL approaches in participating media, however, distracting singularities still remain. We present Virtual Beam Lights (VBLs), a progressive many‐lights algorithm for rendering complex indirect transport paths in, from, and to media. VBLs are efficient and can handle heterogeneous media, anisotropic scattering, and moderately glossy surfaces, while provably converging to ground truth. We inflate ray lights into beam lights with finite thicknesses to eliminate the remaining singularities. Furthermore, we devise several practical schemes for importance sampling the various transport contributions between camera rays, light rays, and surface points. VBLs produce artifact‐free images faster than VRLs, especially when glossy surfaces and/or anisotropic phase functions are present. Lastly, we employ a progressive thickness reduction scheme for VBLs in order to render results that converge to ground truth.     

Regret and quality of life across the adult life span: The influence of disengagement and available future goals.

Two studies examined the associations between life regrets and indicators of quality of life across the adult life span. Given that opportunities to undo regrets decline with age, regret intensity was expected to be inversely associated with subjective well-being and health among older adults. In addition, the research explored protective factors that have the potential to reduce older adults' regret intensity. It was suggested that being disengaged from undoing the consequences of regrets and having many future goals available may reduce older adults' intensity of regret and thereby contribute to a better quality of life. Across both studies, the findings demonstrate that older adults perceived reduced opportunities to undo the consequences of their regrets and that regret intensity predicted a reduced quality of life only among older adults. Furthermore, the findings support the adaptive value of disengagement and available future goals for managing life regrets in older adults. (PsycINFO Database Record (c) 2010 APA, all rights reserved)