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VISUAL ATTENTION PROBABILITY MODEL FOR STEREOSCOPIC VIDEOS ESTIMATED USING STATISTICAL DESIGN OF EXPERIMENTS : 통계적 실험 계획법을 이용하여 추정한 삼차원 동영상의 시각 주의 확률 모델
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 김태정 | - |
dc.contributor.author | 김보은 | - |
dc.date.accessioned | 2017-07-14T02:59:04Z | - |
dc.date.available | 2017-07-14T02:59:04Z | - |
dc.date.issued | 2015-02 | - |
dc.identifier.other | 000000025099 | - |
dc.identifier.uri | https://hdl.handle.net/10371/123129 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 2. 김태정. | - |
dc.description.abstract | Viewers of videos are likely to absorb more information from the part of the screen that attracts visual attention. This fact has lead to the visual attention models that is
being used in producing and evaluating videos. In this paper, we investigate the factors that are significant to visual attention and the mathematical form of the visual attention model, and then estimate the visual attention probability using the statistical design of experiments. The analysis of variance (ANOVA) verifies that the motion velocity, distance from the screen, and amount of defocus blur are the factors that strongly affect human visual attention. Using the response surface modeling (RSM), we create a visual attention score model that concerns the three factors, and from which model we calculate the visual attention probabilities (VAPs) of image pixels. The VAPs are directly applied to existing gradient based 3D effect perception measurement. By giving weights according to our VAPs, more accurate measurement is possible. The performance of the proposed measurement is assessed by comparing them with subjective evaluation as well as with existing methods. The comparison verifies that the proposed measurement outperforms the existing ones. | - |
dc.description.tableofcontents | Abstract
Contents List of Figures List of Tables 1. Introduction 2. Visual Attention Probability (VAP) 2.1 Previous Studies and Motivation 2.2 Factors that Influence the Visual Attention 2.3 Statistical Design of the Experiment and the Visual Attention Score Model 2.3.1 Experiment Design 2.3.2 Analysis of Variance (ANOVA) 2.3.3 Response Surface Modeling (RSM) 2.4 Visual Attention Probability and Its Application 2.4.1 Visual Attention Probability 2.4.2 Application to Movie Frames 3 3D Effect Perception Measurement Using the VAP 3.1 Previous Studies 3.2 Gradient Method with the VAP 3.3 Experiment Results 4 Conclusion Abstract in Korean | - |
dc.format | application/pdf | - |
dc.format.extent | 17271597 bytes | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | Visual attention probability | - |
dc.subject.ddc | 621 | - |
dc.title | VISUAL ATTENTION PROBABILITY MODEL FOR STEREOSCOPIC VIDEOS ESTIMATED USING STATISTICAL DESIGN OF EXPERIMENTS | - |
dc.title.alternative | 통계적 실험 계획법을 이용하여 추정한 삼차원 동영상의 시각 주의 확률 모델 | - |
dc.type | Thesis | - |
dc.contributor.AlternativeAuthor | Boeun Kim | - |
dc.description.degree | Master | - |
dc.citation.pages | v, 38 | - |
dc.contributor.affiliation | 공과대학 전기·컴퓨터공학부 | - |
dc.date.awarded | 2015-02 | - |
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