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논문 기본 정보

자료유형
학술저널
저자정보
Rafiul Hasan Khan (Pukyong National University) Youngsuk Lee (Dongguk University) Suk-Hwan Lee (Tongmyong University) Oh-Jun Kwon (Dongeui University) Ki-Ryong Kwon (Pukyong National University)
저널정보
한국멀티미디어학회 멀티미디어학회논문지 멀티미디어학회논문지 제22권 제5호
발행연도
2019.5
수록면
558 - 572 (15page)

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초록· 키워드

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Anthropomorphism is the attribution of human traits, emotions, or intentions to non-human entities. Anthropomorphic animal face masking is the process by which human characteristics are plotted on the animal kind. In this research, we are proposing a compact system which finds the resemblance between a human face and animal face using Deep Convolutional Neural Network (DCNN) and later applies morphism between them. The whole process is done by firstly finding which animal most resembles the particular human face through a DCNN based animal face classification. And secondly, doing triangulation based morphing between the particular human face and the most resembled animal face. Compared to the conventional manual Control Point Selection system using an animator, we are proposing a Viola-Jones algorithm based Control Point selection process which detects facial features for the human face and takes the Control Points automatically. To initiate our approach, we built our own dataset containing ten thousand animal faces and a fourteen layer DCNN. The simulation results firstly demonstrate that the accuracy of our proposed DCNN architecture outperforms the related methods for the animal face classification. Secondly, the proposed morphing method manages to complete the morphing process with less deformation and without any human assistance.

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ABSTRACT
1. INTRODUCTION
2. RELATED WORKS
3. PROPOSED METHOD
4. RESULTS AND DISCUSSION
5. CONCLUSION
REFERENCES

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UCI(KEPA) : I410-ECN-0101-2019-004-000895211