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Nguyen, Diep Thi Ngoc and Nakayama, Hideki and Okazaki, Naoaki and Sakaeda, Tatsuya (2018) PoB. In: The 26th ACM international conference on Multimedia, October 22-26, 2018, Seoul, Korea.

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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.

Item Type: Conference or Workshop Item (Paper)
Subjects: Information Technology (IT)
Scopus-indexed journals
Divisions: Faculty of Information Technology (FIT)
Depositing User: Ms Diep Nguyen Thi Ngoc
Date Deposited: 10 Dec 2019 15:51
Last Modified: 10 Dec 2019 15:51

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