scholarly journals Comparing surface digitization techniques in palaeontology using visual perceptual metrics and distance computations between 3D meshes

Palaeontology ◽  
2021 ◽  
Author(s):  
Verónica Díez Díaz ◽  
Heinrich Mallison ◽  
Patrick Asbach ◽  
Daniela Schwarz ◽  
Alejandro Blanco
Keyword(s):  
Perceptual Metrics

scholarly journals Batch Decorrelation for Active Metric Learning

2020 ◽  
Author(s):  
Priyadarshini Kumari ◽  
Ritesh Goru ◽  
Siddhartha Chaudhuri ◽  
Subhasis Chaudhuri
Keyword(s):  
Active Learning ◽  
Learning Strategy ◽  
Metric Learning ◽  
Parametric Models ◽  
Distance Metrics ◽  
Learning Approaches ◽  
Fundamental Goal ◽  
Novel Method ◽  
Active Learning Strategy ◽  
Perceptual Metrics

We present an active learning strategy for training parametric models of distance metrics, given triplet-based similarity assessments: object $x_i$ is more similar to object $x_j$ than to $x_k$. In contrast to prior work on class-based learning, where the fundamental goal is classification and any implicit or explicit metric is binary, we focus on perceptual metrics that express the degree of (dis)similarity between objects. We find that standard active learning approaches degrade when annotations are requested for batches of triplets at a time: our studies suggest that correlation among triplets is responsible. In this work, we propose a novel method to decorrelate batches of triplets, that jointly balances informativeness and diversity while decoupling the choice of heuristic for each criterion. Experiments indicate our method is general, adaptable, and outperforms the state-of-the-art.

Free-Classification of Perceptually Similar Speakers With Dysarthria

2014 ◽  
Vol 57 (6) ◽  
pp. 2051-2064 ◽  
Author(s):  
Kaitlin L. Lansford ◽  
Julie M. Liss ◽  
Rebecca E. Norton
Keyword(s):  
Cluster Analysis ◽  
Perceptual Similarity ◽  
Articulation Rate ◽  
Classification Approach ◽  
Perceptual Judgments ◽  
Similarity Judgments ◽  
Vocal Quality ◽  
Free Classification ◽  
Perceptual Metrics

Purpose In this investigation, the construct of perceptual similarity was explored in the dysarthrias. Specifically, we employed an auditory free-classification task to determine whether listeners could cluster speakers by perceptual similarity, whether the clusters mapped to acoustic metrics, and whether the clusters were constrained by dysarthria subtype diagnosis. Method Twenty-three listeners blinded to speakers' medical and dysarthria subtype diagnoses participated. The task was to group together (drag and drop) the icons corresponding to 33 speakers with dysarthria on the basis of how similar they sounded. Cluster analysis and multidimensional scaling (MDS) modeled the perceptual dimensions underlying similarity. Acoustic metrics and perceptual judgments were used in correlation analyses to facilitate interpretation of the derived dimensions. Results Six clusters of similar-sounding speakers and 3 perceptual dimensions underlying similarity were revealed. The clusters of similar-sounding speakers were not constrained by dysarthria subtype diagnosis. The 3 perceptual dimensions revealed by MDS were correlated with metrics for articulation rate, intelligibility, and vocal quality, respectively. Conclusions This study shows (a) feasibility of a free-classification approach for studying perceptual similarity in dysarthria, (b) correspondence between acoustic and perceptual metrics to clusters of similar-sounding speakers, and (c) similarity judgments transcended dysarthria subtype diagnosis.

scholarly journals The independent contribution of voice onset time to perceptual metrics of convergence

2021 ◽  
Vol 1 (4) ◽  
pp. 045205
Author(s):  
Jessamyn Schertz ◽  
Elizabeth K. Johnson ◽  
Melissa Paquette-Smith
Keyword(s):  
Voice Onset Time ◽  
Onset Time ◽  
Independent Contribution ◽  
Perceptual Metrics

Board Information Technology Governance and Business Agility

2021 ◽  
Vol 13 (3) ◽  
pp. 28-49
Author(s):  
Admir Kozlica
Keyword(s):  
Information Technology ◽  
Business Performance ◽  
Test Results ◽  
Critical Elements ◽  
Technology Governance ◽  
Business Agility ◽  
Information Technology Governance ◽  
Enterprise Agility ◽  
And Performance ◽  
Perceptual Metrics

The goal of this paper is to empirically investigate and analyze the board's involvement in the information technology governance (ITG) function and how the ITG degree has implications for enterprise agility and financial performance. The analysis primarily relies on perceptual metrics. That is board members' views on the importance and impact of the decisions considered and made on the business outcome. The contribution is reflected in the relation of several of the most significant enterprise resources in complex conditions. The approach seeks to determine whether enterprise agility and business performance are the result of a higher degree of ITG or are critical elements of contingency. The test results show that enterprise agility has a significant indirect impact between ITG attainment and performance and that predefined IT role factors drive this relationship. The limitation of the research is that the capital market is not sufficiently developed in Bosnia and Herzegovina, and the responsibilities of the IT supervisory and audit bodies are not fully formulated.

Perceptual coders and perceptual metrics

2001 ◽  
Author(s):  
Junqing Chen ◽  
Thrasyvoulos N. Pappas
Keyword(s):  
Perceptual Metrics

Perceptual metrics for character animation

2003 ◽  
Vol 22 (3) ◽  
pp. 537-542 ◽  
Author(s):  
Paul S. A. Reitsma ◽  
Nancy S. Pollard
Keyword(s):  
Character Animation ◽  
Perceptual Metrics

Perceptual metric-guided human image generation

2021 ◽  
pp. 1-11
Author(s):  
Haoran Wu ◽  
Fazhi He ◽  
Yansong Duan ◽  
Xiaohu Yan
Keyword(s):  
State Of The Art ◽  
Transfer Task ◽  
Generative Adversarial Networks ◽  
Perceptual Quality ◽  
Image Generation ◽  
Migration Process ◽  
Adversarial Networks ◽  
Human Image ◽  
Detection Score ◽  
Perceptual Metrics

Pose transfer, which synthesizes a new image of a target person in a novel pose, is valuable in several applications. Generative adversarial networks (GAN) based pose transfer is a new way for person re-identification (re-ID). Typical perceptual metrics, like Detection Score (DS) and Inception Score (IS), were employed to assess the visual quality after generation in pose transfer task. Thus, the existing GAN-based methods do not directly benefit from these metrics which are highly associated with human ratings. In this paper, a perceptual metrics guided GAN (PIGGAN) framework is proposed to intrinsically optimize generation processing for pose transfer task. Specifically, a novel and general model-Evaluator that matches well the GAN is designed. Accordingly, a new Sort Loss (SL) is constructed to optimize the perceptual quality. Morevover, PIGGAN is highly flexible and extensible and can incorporate both differentiable and indifferentiable indexes to optimize the attitude migration process. Extensive experiments show that PIGGAN can generate photo-realistic results and quantitatively outperforms state-of-the-art (SOTA) methods.

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