한국과학예술포럼 (Korea Science and Art Forum)

한국과학예술융합학회 (The Korean Society of Science & Art)
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영상 구성 파라미터 추출을 위한 융합 분석 알고리듬 연구

Convergence Analysis Algorithm Study for Extracting Image Configuration Parameters

  • 맹채정 (중앙대학교 창의ICT공과대학) ;
  • 하동환 (중앙대학교 소프트웨어대학)
  • 투고 : 2019.05.13
  • 발행 : 2019.06.30
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구는 영상콘텐츠 제작과정에서 배경음악 선정의 자동화를 위하여 영상의 특성을 분류, 분석할 수 있는 프로그램을 구성하였다. 연구 결과 및 내용은 다음과 같다. 영상의 특성은 '주제 범주', '감정', '픽셀 움직임 속도', '색상', '등장인물' 로 선정하며, '주제 범주'와 '감정'은 Microsoft사의 Azure Video Indexer를, '픽셀 움직임 속도'는 Optical flow, '색상'은 Image Histogram, '등장인물'은 CNN (Convolutional Neural Network)을 활용하여 데이터를 추출하였다. 이러한 본 연구의 결과는 최근 주목을 받고있는 '인터넷 1인 방송 크리에이터'들의 콘텐츠 제작과정에서 배경음악 매칭을 위한 영상 특성 분석이 이루어졌다는 점에서 의의가 있다.

This study was conducted to organize a program to classify and analyze the characteristics of images for the automation of background music selection in the video content production process. The results and contents of the study are as follows: video characteristics are selected as subject category, emotion, pixel motion speed, color, and character material. Subject categories and feelings were extracted using Microsoft's Azure Video Indexer, Pixel Movement Speed was an Optional flow, Color was an Image Histogram for Image, and character materials was CNN(Convolutional Neural Network). The results of this study are significant in that video analysis was conducted to match background music in the recent content production process of 'Internet One-person Broadcasting Creators'.

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참고문헌

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