메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Bai yu (Tongmyong University) Sang-Yun Park (Tongmyong University) Yun-Sik Kim (Tongmyong University) In-Gab Jeong (Kyungpook Provincial College) Soo-Yol Ok (Tongmyong University) Eung-Joo Lee (Tongmyong University)
저널정보
한국멀티미디어학회 멀티미디어학회논문지 멀티미디어학회논문지 제14권 제2호
발행연도
2011.2
수록면
182 - 193 (12page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

이 논문의 연구 히스토리 (2)

초록· 키워드

오류제보하기
The aim of this paper is to present the methodology for hand tracking and hand gesture recognition. The detected hand and gesture can be used to implement the non-contact mouse. We had developed a MP3 player using this technology controlling the computer in stead of mouse. In this algorithm, we first do a pre-processing to every frame which including Lighting compensation and background filtration to reducing the adverse impact on correctness of hand tracking and hand gesture recognition. Secondly, YCbCr skin-color likelihood algorithm is used to detecting the hand area. Then, we used Continuously Adaptive Mean Shift (CAMSHIFT) algorithm to tracking hand. As the formula-based region of interest is square, the hand is closer to rectangular. We have improved the formula of the search window to get a much suitable search window for hand. And then, Support Vector Machines (SVM) algorithm is used for hand gesture recognition. For training the system, we collected 1500 hand gesture pictures of 5 hand gestures. Finally we have performed extensive experiment on a Windows XP system to evaluate the efficiency of the proposed scheme. The hand tracking correct rate is 96% and the hand gestures average correct rate is 95%.

목차

ABSTRACT
1. INTRODUCTION
2. LIGHTING COMPENSATION AND BACKGROUND FILTRATION
3. HAND DETECTION
4. HAND TRACKING BASED ON CAMSHIFT ALGORITHM
5. HAND GESTURE RECOGNITION BASED ON SUPPORT VECTOR MACHINE
6. EXPERIMENTAL RESULTS
7. CONCLUSIONS
REFERENCES

참고문헌 (2)

참고문헌 신청

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2013-004-000788304