889 research outputs found

    Integral Human Pose Regression

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    State-of-the-art human pose estimation methods are based on heat map representation. In spite of the good performance, the representation has a few issues in nature, such as not differentiable and quantization error. This work shows that a simple integral operation relates and unifies the heat map representation and joint regression, thus avoiding the above issues. It is differentiable, efficient, and compatible with any heat map based methods. Its effectiveness is convincingly validated via comprehensive ablation experiments under various settings, specifically on 3D pose estimation, for the first time

    On the Schoenberg Transformations in Data Analysis: Theory and Illustrations

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    The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A simple distance-based discriminant algorithm illustrates the theory, intimately connected to the Gaussian kernels of Machine Learning

    Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm

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    The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a 1963 publication. It has also been generalized in various ways. However there are different interpretations in the literature and there are different implementations of the Ward agglomerative algorithm in commonly used software systems, including differing expressions of the agglomerative criterion. Our survey work and case studies will be useful for all those involved in developing software for data analysis using Ward's hierarchical clustering method.Comment: 20 pages, 21 citations, 4 figure

    Microsatellite discovery in an insular amphibian (Grandisonia alternans) with comments on cross-species utility and the accuracy of locus identification from unassembled Illumina data

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    The Seychelles archipelago is unique among isolated oceanic islands because it features an endemic radiation of caecilian amphibians (Gymnophiona). In order to develop population genetics resources for this system, we identified microsatellite loci using unassembled Illumina MiSeq data generated from a genomic library of Grandisonia alternans, a species that occurs on multiple islands in the archipelago. Applying a recently described method (PALFINDER) we identified 8001 microsatellite loci that were potentially informative for population genetics analyses. Of these markers, we screened 60 loci using five individuals, directly sequenced several amplicons to confirm their identity, and then used eight loci to score allele sizes in 64 G. alternans individuals originating from five islands. A number of these individuals were sampled using non-lethal methods, demonstrating the efficacy of non-destructive molecular sampling in amphibian research. Although two loci satisfied our criteria as diploid, neutrally evolving loci with the statistical power to detect population structure, our success in identifying reliable loci was very low. Additionally, we discovered some issues with primer redundancy and differences between Illumina and Sanger sequences that suggest some Illumina-inferred loci are invalid. We investigated cross-species utility for eight loci and found most could be successfully amplified, sequenced and aligned across other species and genera of caecilians from the Seychelles. Thus, our study in part supported the validity of using PALFINDER with unassembled reads for microsatellite discovery within and across species, but importantly identified major limitations to applying this approach to small datasets (ca. 1 million reads) and loci with small tandem repeat sizes

    Predicting Head Pose in Dyadic Conversation

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    Natural movement plays a significant role in realistic speech animation. Numerous studies have demonstrated the contribution visual cues make to the degree we, as human observers, find an animation acceptable. Rigid head motion is one visual mode that universally co-occurs with speech, and so it is a reasonable strategy to seek features from the speech mode to predict the head pose. Several previous authors have shown that prediction is possible, but experiments are typically confined to rigidly produced dialogue. Expressive, emotive and prosodic speech exhibit motion patterns that are far more difficult to predict with considerable variation in expected head pose. People involved in dyadic conversation adapt speech and head motion in response to the others’ speech and head motion. Using Deep Bi-Directional Long Short Term Memory (BLSTM) neural networks, we demonstrate that it is possible to predict not just the head motion of the speaker, but also the head motion of the listener from the speech signal

    Characterizing the universal rigidity of generic frameworks

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    A framework is a graph and a map from its vertices to E^d (for some d). A framework is universally rigid if any framework in any dimension with the same graph and edge lengths is a Euclidean image of it. We show that a generic universally rigid framework has a positive semi-definite stress matrix of maximal rank. Connelly showed that the existence of such a positive semi-definite stress matrix is sufficient for universal rigidity, so this provides a characterization of universal rigidity for generic frameworks. We also extend our argument to give a new result on the genericity of strict complementarity in semidefinite programming.Comment: 18 pages, v2: updates throughout; v3: published versio

    Intra- and inter-individual genetic differences in gene expression

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    Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

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    The International-Trade Network: Gravity Equations and Topological Properties

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    This paper begins to explore the determinants of the topological properties of the international - trade network (ITN). We fit bilateral-trade flows using a standard gravity equation to build a "residual" ITN where trade-link weights are depurated from geographical distance, size, border effects, trade agreements, and so on. We then compare the topological properties of the original and residual ITNs. We find that the residual ITN displays, unlike the original one, marked signatures of a complex system, and is characterized by a very different topological architecture. Whereas the original ITN is geographically clustered and organized around a few large-sized hubs, the residual ITN displays many small-sized but trade-oriented countries that, independently of their geographical position, either play the role of local hubs or attract large and rich countries in relatively complex trade-interaction patterns
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