Semantic Analysis of (Reflectional) Visual Symmetry: A Human-Centred Computational Model for Declarative Explainability

05/31/2018
by   Jakob Suchan, et al.
0

We present a computational framework for the semantic interpretation of symmetry in naturalistic scenes. Key features include a human-centred representation, and a declarative, explainable interpretation model supporting deep semantic question-answering founded on an integration of methods in knowledge representation and computer vision. In the backdrop of the visual arts, we showcase the framework's capability to generate human-centred, queryable, relational structures, also evaluating the framework with an empirical study on the human perception of visual symmetry. Our framework represents and is driven by the application of foundational Vision and KR methods in the psychological and social sciences.

READ FULL TEXT

page 1

page 2

page 3

page 4

page 5

page 6

research
04/11/2017

Beyond Planar Symmetry: Modeling human perception of reflection and rotation symmetries in the wild

Humans take advantage of real world symmetries for various tasks, yet ca...
research
08/25/2017

Identifying Mirror Symmetry Density with Delay in Spiking Neural Networks

The ability to rapidly identify symmetry and anti-symmetry is an essenti...
research
05/31/2019

Out of Sight But Not Out of Mind: An Answer Set Programming Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving

We demonstrate the need and potential of systematically integrated visio...
research
10/10/2022

Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs

Answering factual questions with temporal intent over knowledge graphs (...
research
10/18/2021

On completing a measurement model by symmetry

An appeal for symmetry is made to build established notions of specific ...
research
07/19/2022

Computer Vision to the Rescue: Infant Postural Symmetry Estimation from Incongruent Annotations

Bilateral postural symmetry plays a key role as a potential risk marker ...
research
05/28/2021

FAST CAT: Collaborative Data Entry and Curation for Semantic Interoperability in Digital Humanities

Descriptive and empirical sciences, such as History, are the sciences th...

Please sign up or login with your details

Forgot password? Click here to reset