• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1621-1626
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• 2017

This study conducts data visualization of common climax patterns of Korean blockbuster films to analyze shots and evaluate scene (subplot unit) arrangement. For this purpose, a model of editing patterns is used to analyze how many climax patterns a film contains. Moreover, a system, which automatically collects shot images and classifies shot sizes of collected data, is designed to demonstrate that a single scene is composed based on a climax pattern. As a scene is a subplot and thus its arrangement cannot fully be analyzed only by climax patterns, dialogues of starring actors are also used to identify scenes, and the result is compared with data visualization results. It detects dialogues between particular actors and visualizes dialogue formation in a network form. Such network visualization enables the arrangement of main subplots to be analyzed, and the box office performance of a film can be explained by the density of subplots. The study of two types comparison analysis is expected to contribute to planning, plotting, and producing films.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.983-991
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• 2019

This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.

• Fashion & Textile Research Journal
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• v.23 no.4
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• pp.469-479
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• 2021

This case study investigates fashion brands that have entered the pet fashion market. A total of 25 cases were identified and analyzed from three perspectives: 1) product types, size systems, prices, 2) design aspects, fabrics, patterns, styles, and 3) marketing strategies. The study results are as follows. First, the product types of pet fashion are not diverse, and only the sizes of small dogs can be found. However, there is a significant price difference between brands. Second, knitted fabrics with good elasticity are mainly used for pet fashion products, and patterns incorporating their brands are extremely common. The style is casual and sporty. Third, marketing strategies should include a new line within a brand or launch a single specialized brand as a one-shot test for consumer reaction. Additionally, it has been expanded and presented as a family look to meet the needs of the petfam. Further, existing fashion brands and retail-based brands select diverse small-scale dog fashion product brands and expand their operation as a dog lifestyle total selectional shop. Therefore, brands entering the future should consider strategies such as size segmentation, product diversification, and premium price of high-quality materials that help market products such as the expansion or promotion of existing brands.