relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3790/
title: PoB: Toward Reasoning Patterns of Beauty in Image Data
creator: Nguyen, Diep Thi Ngoc
creator: Nakayama, Hideki
creator: Okazaki, Naoaki
creator: Sakaeda, Tatsuya
subject: Information Technology (IT)
description: Aiming to develop of computational grammar system for visual information, we design a 4-tier framework that consists of four levels of 'visual grammar of images.' As a first step of realization, we propose a new dataset, named the PoB dataset, in which each image is annotated with multiple labels of armature patterns that compose the pictorial scene. The PoB dataset includes of a 10,000-painting dataset for art and a 4,959-image dataset for photography. In this paper, we discuss the consistency analysis of our dataset and its applicability. We also demonstrate how the armature patterns in the PoB dataset are useful in assessing aesthetic quality of images, and how well a deep learning algorithm can recognize these patterns. This paper seeks to set a new direction in image understanding with a more holistic approach beyond discrete objects and in aesthetic reasoning with a more interpretative way.
date: 2018
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3790/1/%5B2018%20acmmm%5Dpob_diep.pdf
identifier:   Nguyen, Diep Thi Ngoc and Nakayama, Hideki and Okazaki, Naoaki and Sakaeda, Tatsuya  (2018) PoB: Toward Reasoning Patterns of Beauty in Image Data.  In: The 26th ACM international conference on Multimedia, October 22-26, 2018, Seoul, Republic of Korea.     
relation: http://dx.doi.org/10.1145/3240508.3240711
relation: 10.1145/3240508.3240711