지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2012.10
- 수록면
- 1,480 - 1,485 (6page)
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초록· 키워드
오류제보하기
Intelligent human-robot interface helps a mobile robot to extract external information and interact with a user. User identification information allows a robot to generate appropriate behaviors and make personalized human-robot interaction (PHRI) more natural and safe. Most of service robots move around in various application settings, and biometric features always change during relative movements. In this work, a fusion recognition system based on face and speaker classifiers is designed to achieve the user recognition in various environments. We propose a method to fuse face and speech recognition results based on the concept of confidence indices. Through the derived confidence indices, the system combines the two classifiers and gives improved recognition results. Experiments on a laboratory home service robot show that person recognition rates in 15 environmental situations all outperform those of using single modality.
목차
Abstract
1. INTRODUCTION
2. SYSTEM ARCHITECTURE OF BIMODALUSER RECOGNITION
3. FUSION RECOGNITION STRATEGY
4. EXPERIMENTAL RESULTS
5. CONCLUSION
REFERENCES
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