According to the limitations of a single measurement algorithm in the current 3D models’ viewpoint extraction, this essay puts forward a viewpoint extraction algorithm based on AdaBoost iterative algorithm, which can make the features adaptive automatically. It, firstly, extracts 3D models’ feature descriptor and feature vector in the model library and adopts AdaBoost iterative algorithm to establish rules about classification and matching from geometric features and various viewpoint extraction algorithm; then, it constructs decision classifier in order to extract optimal viewpoint. In query process, the model obtains viewpoint extraction algorithm which can suit its geometric feature through decision classifier and then gets its best view by calculation. The experimental result shows this algorithm extraction effect is superior to the one by a single measurement algorithm.
목차
Abstract 1. Introduction 2. Research Method Summary 3. Geometric Features and Viewpoint Extraction 3.1. Extraction of SDF Feature Descriptor and Eigenvector 3.2. Construction of Viewpoint Extraction Algorithm Library 3.3. Construction of Decision Classifier and Viewpoint Extraction 4. Examples and Analysis 4.1. Analysis of Subjective Visual Sense Matching 4.2. Statistical Analysis of Function Comparison 4.3. Analysis of Algorithm Stability 5. Conclusions References
보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Multimedia and Ubiquitous Engineering
간기
월간
pISSN
1975-0080
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.11 No.1