Scale-invariant vote-based 3D recognition and registration from point clouds

This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a (real and) challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2013 Springer-Verlag Berlin Heidelberg.

Syllable language models for Mandarin speech recognition: exploiting character language models.

Mandarin Chinese is based on characters which are syllabic in nature and morphological in meaning. All spoken languages have syllabiotactic rules which govern the construction of syllables and their allowed sequences. These constraints are not as restrictive as those learned from word sequences, but they can provide additional useful linguistic information. Hence, it is possible to improve speech recognition performance by appropriately combining these two types of constraints. For the Chinese language considered in this paper, character level language models (LMs) can be used as a first level approximation to allowed syllable sequences. To test this idea, word and character level n-gram LMs were trained on 2.8 billion words (equivalent to 4.3 billion characters) of texts from a wide collection of text sources. Both hypothesis and model based combination techniques were investigated to combine word and character level LMs. Significant character error rate reductions up to 7.3% relative were obtained on a state-of-the-art Mandarin Chinese broadcast audio recognition task using an adapted history dependent multi-level LM that performs a log-linearly combination of character and word level LMs. This supports the hypothesis that character or syllable sequence models are useful for improving Mandarin speech recognition performance.

A printable optical time-temperature integrator based on shape memory in a chiral nematic polymer network

An optical and irreversible temperature sensor (e.g., a time-temperature integrator) is reported based on a mechanically embossed chiral-nematic polymer network. The polymer consists of a chemical and a physical (hydrogen-bonded) network and has a reflection band in the visible wavelength range. The sensors are produced by mechanical embossing at elevated temperatures. A relative large compressive deformation (up to 10%) is obtained inducing a shift to shorter wavelength of the reflection band (>30 nm). After embossing, a temperature sensor is obtained that exhibits an irreversible optical response. A permanent color shift to longer wavelengths (red) is observed upon heating of the polymer material to temperatures above the glass transition temperature. It is illustrated that the observed permanent color shift is related to shape memory in the polymer material. The films can be printed on a foil, thus showing that these sensors are potentially interesting as time-temperature integrators for applications in food and pharmaceutical products. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spontaneous emission from radiative chiral nematic liquid crystals at the photonic band-gap edge: An investigation into the role of the density of photon states near resonance

In this article, we investigate the spontaneous emission properties of radiating molecules embedded in a chiral nematic liquid crystal, under the assumption that the electronic transition frequency is close to the photonic edge mode of the structure, i.e., at resonance. We take into account the transition broadening and the decay of electromagnetic field modes supported by the so-called "mirrorless"cavity. We employ the Jaynes-Cummings Hamiltonian to describe the electron interaction with the electromagnetic field, focusing on the mode with the diffracting polarization in the chiral nematic layer. As known in these structures, the density of photon states, calculated via the Wigner method, has distinct peaks on either side of the photonic band gap, which manifests itself as a considerable modification of the emission spectrum. We demonstrate that, near resonance, there are notable differences between the behavior of the density of states and the spontaneous emission profile of these structures. In addition, we examine in some detail the case of the logarithmic peak exhibited in the density of states in two-dimensional photonic structures and obtain analytic relations for the Lamb shift and the broadening of the atomic transition in the emission spectrum. The dynamical behavior of the atom-field system is described by a system of two first-order differential equations, solved using the Green's-function method and the Fourier transform. The emission spectra are then calculated and compared with experimental data. © 2013 American Physical Society.

Spontaneous emission from radiative chiral nematic liquid crystals at the photonic band-gap edge: an investigation into the role of the density of photon states near resonance.

In this article, we investigate the spontaneous emission properties of radiating molecules embedded in a chiral nematic liquid crystal, under the assumption that the electronic transition frequency is close to the photonic edge mode of the structure, i.e., at resonance. We take into account the transition broadening and the decay of electromagnetic field modes supported by the so-called "mirrorless"cavity. We employ the Jaynes-Cummings Hamiltonian to describe the electron interaction with the electromagnetic field, focusing on the mode with the diffracting polarization in the chiral nematic layer. As known in these structures, the density of photon states, calculated via the Wigner method, has distinct peaks on either side of the photonic band gap, which manifests itself as a considerable modification of the emission spectrum. We demonstrate that, near resonance, there are notable differences between the behavior of the density of states and the spontaneous emission profile of these structures. In addition, we examine in some detail the case of the logarithmic peak exhibited in the density of states in two-dimensional photonic structures and obtain analytic relations for the Lamb shift and the broadening of the atomic transition in the emission spectrum. The dynamical behavior of the atom-field system is described by a system of two first-order differential equations, solved using the Green's-function method and the Fourier transform. The emission spectra are then calculated and compared with experimental data.

User target intention recognition from cursor position using kalman filter

This paper discusses user target intention recognition algorithms for pointing - clicking tasks to reduce users' pointing time and difficulty. Predicting targets by comparing the bearing angles to targets proposed as one of the first algorithms [1] is compared with a Kalman Filter prediction algorithm. Accuracy and sensitivity of prediction are used as performance criteria. The outcomes of a standard point and click experiment are used for performance comparison, collected from both able-bodied and impaired users. © 2013 Springer-Verlag Berlin Heidelberg.

Multi scale shape index for 3D object recognition

We present Multi Scale Shape Index (MSSI), a novel feature for 3D object recognition. Inspired by the scale space filtering theory and Shape Index measure proposed by Koenderink & Van Doorn [6], this feature associates different forms of shape, such as umbilics, saddle regions, parabolic regions to a real valued index. This association is useful for representing an object based on its constituent shape forms. We derive closed form scale space equations which computes a characteristic scale at each 3D point in a point cloud without an explicit mesh structure. This characteristic scale is then used to estimate the Shape Index. We quantitatively evaluate the robustness and repeatability of the MSSI feature for varying object scales and changing point cloud density. We also quantify the performance of MSSI for object category recognition on a publicly available dataset. © 2013 Springer-Verlag.

Optically activated shutter using a photo-tunable short-pitch chiral nematic liquid crystal

We report the demonstration of an optically activated shutter based upon a short-pitch chiral nematic liquid crystal (LC) device sandwiched between crossed polarizers. This LC is comprised of photo-active chiral dopants. In the trans-state, the LC appears dark between crossed polarizers due to the very short pitch. As the pitch is extended through exposure to ultraviolet light, the device becomes transmissive reaching a maximum for a particular value of the pitch. As a result, it is possible to switch between the light and dark states by subjecting the device to visible light so as to cause a cis-trans photo-isomerisation. © 2013 AIP Publishing LLC.

Kernelized log linear models for continuous speech recognition

Large margin criteria and discriminative models are two effective improvements for HMM-based speech recognition. This paper proposed a large margin trained log linear model with kernels for CSR. To avoid explicitly computing in the high dimensional feature space and to achieve the nonlinear decision boundaries, a kernel based training and decoding framework is proposed in this work. To make the system robust to noise a kernel adaptation scheme is also presented. Previous work in this area is extended in two directions. First, most kernels for CSR focus on measuring the similarity between two observation sequences. The proposed joint kernels defined a similarity between two observation-label sequence pairs on the sentence level. Second, this paper addresses how to efficiently employ kernels in large margin training and decoding with lattices. To the best of our knowledge, this is the first attempt at using large margin kernel-based log linear models for CSR. The model is evaluated on a noise corrupted continuous digit task: AURORA 2.0. © 2013 IEEE.

Zebrafish peptidoglycan recognition protein SC (zfPGRP-SC) mediates multiple intracellular signaling pathways

Insect PGRPs can function as bacterial recognition molecules triggering proteolytic and/or signal transduction pathways, with the resultant production of antimicrobial peptides. To explore if zebrafish peptidoglycan recognition protein SC (zfPGRP-SC) has such effects, RNA interference (siRNA) and high-density oligonucleotide microarray analysis were used to identify differentially expressed genes regulated by zfPGRP-SC. The mRNA levels for a set of genes involved in Toll-like receptor signaling pathway, such as TLRs, SARM, MyD88, TRAF6 and nuclear factor (NF)-kappa B2 (p100/p52), were examined by quantitative RT-PCR (QT-PCR). The results from the arrays and QT-PCR showed that the expression of 133 genes was involved in signal transduction pathways, which included Toll-like receptor signaling, Wnt signaling, BMP signaling, insulin receptor signaling, TGF-beta signaling, GPCR signaling, small GTPase signaling, second-messenger-mediated signaling, MAPK signaling, JAK/STAT signaling, apoptosis and anti-apoptosis signaling and other signaling cascades. These signaling pathways may connect with each other to form a complex network to regulate not just immune responses but also other processes such as development and apoptosis. When transiently over-expressed in HEK293T cells, zfPGRP-SC inhibited NF-kappa B activity with and without lipopolysacharide (LPS) stimulation. (C) 2008 Elsevier Ltd. All rights reserved.

RNAi suppression of zebrafish peptidoglycan recognition protein 6 (zfPGRP6) mediated differentially expressed genes involved in Toll-like receptor signaling pathway and caused increased susceptibility to Flavobacterium columnare

In Drosophila, Toll signaling cascade, which resembles the mammalian Toll-like receptor (TLR)/IL-1R signaling pathways and regulates the expression of anti-microbial peptide genes, mainly relies on peptidoglycan recognition proteins (PGRPs) for the detection of bacterial pathogens. To explore the effect of zebrafish peptidoglycan recognition protein 6 (zfPGRP6) on Toll-like receptor signaling pathway, RNA interference (siRNA) and real time quantitative PCR (RQ-PCR) methods were used to identify differentially expressed genes regulated by zfPGRP6. The target genes included TLR2, TLR3, TLR5, TLR7, TLR8, IL1R, Sterile-alpha and Armadillo motif containing protein (SARM), myeloid differentiation factor 88 (MyD88) and nuclear factor (NF)-kappa B2 (p100/p52). The results of RQ-PCR showed that RNAi-mediated Suppression of zfPGRP6 significantly down-regulated the expression of TLR2, TLR5, IL1R, SARM, MyD88 and p100/p52. The expression of beta-defensin-1 was also down-regulated in those embryos silenced by zfPGRP6. In challenge experiments to determine the anti-bacterial response to Gram-negative bacteria, RNAi knock-down of zfPGRP6 markedly increased susceptibility to Flavobacterium columnare. (C) 2008 Elsevier B.V. All rights reserved.