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
- 2014.10
- 수록면
- 94 - 98 (5page)
이용수
초록· 키워드
오류제보하기
An approach to human behavior recognition is presented in this paper. The system is separated into two parts: human action recognition and object recognition. The estimation result is composed of a simple action “Pointing” and a virtual assumed object, which has two attributes, one is “current status” and the other is “acceptable behavior”. Once the human action and object are recognized, then detect whether a vector calculated by human elbow intersected the object. If the vector is intersected, then estimate human behavior by combining the human action and the object attribute. The artificial neural network (ANN) is discussed as a main part of the current research. Whole ANN processing is simulated by Octave 3.8, the human actions are captured by Microsoft Kinect, and a human model is built by using human joint data.
목차
Abstract
1. INTRODUCTION
2. OUTLINE OF ESTIMATION SYSTEM
3. DEFINED SPACE AND OBJECT
4. HUMAN ACTION RECOGNITION
5. ESTIMATING HUMAN BEHAVIOR
6. CONCLUSIONS AND FUTURE RESEARCH
REFERENCES
참고문헌 (0)
참고문헌 신청이 논문의 저자 정보
최근 본 자료
댓글(0)
0