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SCENE CLASSIFICATION FOR DEPTH ASSIGNMENT : 깊이 정보를 부여하기 위한 이미지 분류
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- Authors
- Advisor
- 김태정
- Major
- 공과대학 전기·정보공학부
- Issue Date
- 2016-02
- Publisher
- 서울대학교 대학원
- Keywords
- features for scene classification ; scene depth assignment ; 2D-to-3D conversion ; vanishing point detection ; distribution of color and edge
- Description
- 학위논문 (석사)-- 서울대학교 대학원 : 전기·정보공학부, 2016. 2. 김태정.
- Abstract
- Due to development of 3D display technology, industries related 3D have been grown. For this reason, the demand of 3D contents increases, but there is a short sup- ply of 3D contents. Consequently, research on 2D-to-3D conversion is underway. In 2D-to-3D conversion, the depth information of scene is obtained through an analysis of several depth cues on input sequence and the depth map corresponding to a scene can be generated by combining several depth cues and assigning an appropriate depth level. Scene classification for depth assignment is needed in this process. This paper classifies a scene into landscape, linear perspective, and normal type automatically. The proposed method analyzes landscape type and found there is a relation between image pattern and distribution of color and edge, and suggest the criteria for clas- sification. Moreover, the other criteria for linear perspective classification based on vanishing point detection is proposed. To verify performance, the proposed features are fed into a linear SVM classifier, and 651 images are used. Experiment results show that the algorithm has an advantages in performance by about 13%.
- Language
- English
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