개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
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.
이용수
초록· 키워드
오류제보하기
Objective: This study aims to find suitable types and styles for gesture interaction as remote control on smart TVs.
Background: Smart TV is being developed rapidly in the world, and gesture interaction has a wide range of research areas, especially based on vision techniques. However, most studies are focused on the gesture recognition technology. Also, not many previous studies of gestures types and styles on smart TVs were carried out. Therefore, it is necessary to check what users prefer in terms of gesture types and styles for each operation command.
Method: We conducted an experiment to extract the target user manipulation commands required for smart TVs and select the corresponding gestures. To do this, we looked at gesture styles people use for every operation command, and checked whether there are any gesture styles they prefer over others. Through these results, this study was carried out with a process selecting smart TV operation commands and gestures.
Results: Eighteen TV commands have been used in this study. With agreement level as a basis, we compared the six types of gestures and five styles of gestures for each command. As for gesture type, participants generally preferred a gesture of Path-Moving type. In the case of Pan and Scroll commands, the highest agreement level(1.00) of 18 commands was shown. As for gesture styles, the participants preferred a manipulative style in 11 commands (Next, Previous, Volume up, Volume down, Play, Stop, Zoom in, Zoom out, Pan, Rotate, Scroll).
Conclusion: By conducting an analysis on user-preferred gestures, nine gesture commands are proposed for gesture control on smart TVs. Most participants preferred Path-Moving type and Manipulative style gestures based on the actual operations.
Application: The results can be applied to a more advanced form of the gestures in the 3D environment, such as a study on VR. The method used in this study will be utilized in various domains.
Background: Smart TV is being developed rapidly in the world, and gesture interaction has a wide range of research areas, especially based on vision techniques. However, most studies are focused on the gesture recognition technology. Also, not many previous studies of gestures types and styles on smart TVs were carried out. Therefore, it is necessary to check what users prefer in terms of gesture types and styles for each operation command.
Method: We conducted an experiment to extract the target user manipulation commands required for smart TVs and select the corresponding gestures. To do this, we looked at gesture styles people use for every operation command, and checked whether there are any gesture styles they prefer over others. Through these results, this study was carried out with a process selecting smart TV operation commands and gestures.
Results: Eighteen TV commands have been used in this study. With agreement level as a basis, we compared the six types of gestures and five styles of gestures for each command. As for gesture type, participants generally preferred a gesture of Path-Moving type. In the case of Pan and Scroll commands, the highest agreement level(1.00) of 18 commands was shown. As for gesture styles, the participants preferred a manipulative style in 11 commands (Next, Previous, Volume up, Volume down, Play, Stop, Zoom in, Zoom out, Pan, Rotate, Scroll).
Conclusion: By conducting an analysis on user-preferred gestures, nine gesture commands are proposed for gesture control on smart TVs. Most participants preferred Path-Moving type and Manipulative style gestures based on the actual operations.
Application: The results can be applied to a more advanced form of the gestures in the 3D environment, such as a study on VR. The method used in this study will be utilized in various domains.
목차
1. Introduction
2. Gesture Types and Command Selection
3. Method
4. Results
5. Discussion
6. Conclusion
References
참고문헌 (22)
참고문헌 신청
Baudel, T. and Beaudouin-Lafon, M., Charade: remote control of objects using free-hand gestures, Communications of the ACM, 36(7), 28-35, 1993.
Bolt, R.A. and Herranz, E., Two-handed gesture in multi-modal natural dialog, In Proceedings of the 5th annual ACM symposium on User interface software and technology, 7-14, ACM, 1992.
Cesar, P. and Chorianopoulos, K., The evolution of TV systems, content, and users toward interactivity, Foundations and Trends in Human-Computer Interaction, 2(4), 279-373, 2009.
Choi, E., Kwon, S., Lee, D., Lee, H. and Chung, M.K., Can user-derived gesture be considered as the best gesture for a command?: Focusing on the commands for smart home system, In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 56(1), 1253-1257, 2012.
Karam, M. and Schraefel, M.C., A taxonomy of gestures in human computer interactions, 2005.
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
[조흡의 영화이야기] <최악의 하루>: 소통을 가능케 하는 몸짓
대한토목학회지
2017 .03
-
Continuous gesture recognition by using gesture spotting
제어로봇시스템학회 국제학술대회 논문집
2016 .10
-
An Application for Translation of World-wide Gestures
대한전자공학회 학술대회
2017 .01
-
Hand Gesture Segmentation Method using a Wrist-Worn Wearable Device
대한인간공학회지
2015 .10
-
Hand based Gesture Recognition inside a car through IR-UWB Radar
대한전자공학회 학술대회
2017 .01
-
A Structure and Framework for Sign Language Interaction
대한인간공학회지
2015 .10
-
게임 어플리케이션을 위한 컨볼루션 신경망 기반의 실시간 제스처 인식 연구
멀티미디어학회논문지
2017 .05
-
Recognition of Natural Hand Gestures Using Bidirectional Long Short-Term Memory Model
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS
2018 .12
-
실내 모바일 로봇 조작을 위한 손 제스처 조작 방식 제안 및 구현
제어로봇시스템학회 논문지
2025 .01
-
2단계 히든마코프 모델을 이용한 제스쳐의 성능향상 연구
제어로봇시스템학회 논문지
2015 .11
-
A Unit Touch Gesture Model of Performance Time Prediction for Mobile Devices
대한인간공학회지
2016 .08
-
GESTURE MODULE 최적 설계를 위한 광해석
한국자동차공학회 추계학술대회 및 전시회
2015 .11
-
시 공간 정규화를 통한 딥 러닝 기반의 3D 제스처 인식
멀티미디어학회논문지
2018 .05
-
Proposal of Camera Gesture Recognition System Using Motion Recognition Algorithm
전기전자학회논문지
2022 .03
-
주거 공간에서의 3차원 핸드 제스처 인터페이스에 대한 사용자 요구사항
대한산업공학회지
2015 .10
-
Using Bacteria Foraging Optimization in Gesture Reconfiguration from Joint Failure for Semi-Humanoid Robot
제어로봇시스템학회 국제학술대회 논문집
2019 .10
-
컴퓨터 제어를 위한 딥러닝 기반의 Hand-gesture 인식 시스템
Proceedings of KIIT Conference
2022 .12
-
Hand Gesture Recognition Using an Infrared Proximity Sensor Array
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS
2015 .09
-
Hand Gesture Recognition Suitable for Wearable Devices using Flexible Epidermal Tactile Sensor Array
Journal of Electrical Engineering & Technology
2018 .07
-
Proposal of Image Detection Algorithm to Implement Hand Gestures
전기전자학회논문지
2018 .12
이 논문의 저자 정보
이 논문과 함께 이용한 논문
스마트 TV 리모컨 인터랙션 유형별 사용성 비교 연구
임영재
대한인간공학회지
2018
.12
손 제스처 인식에 기반한 Virtual Block 게임 인터페이스
윤민호
,
김윤제
,
김태영
한국게임학회 논문지
2017
.12
터치패드를 이용한 통합 리모컨에 관한 연구
임지용
,
권동현
,
오암석
한국컴퓨터정보학회 학술발표논문집
2016
.01
PC 사용자 경험에 기초한 IPTV UI 구현 방안
이지원
,
김문희
,
노정자
한국통신학회 학술대회논문집
2009
.06
스마트TV를 위한 개인 맞춤형 사용자 인터페이스 설계
최성욱
,
김태석
한국정보과학회 학술발표논문집
2012
.06
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-ECN-0101-2018-020-000866381