건물 배치 전자도면을 이용한 모바일 폰의 피사체 인지 방법

다국어 초록 (Multilingual Abstract)

As the techniques of electronic and information are advancing, the computing power of a smart phone is becoming more powerful and the storage capacity of a smart phone is becoming larger. As the result, various new useful services are becoming available on smart phones. The context-aware service and mobile augmented reality have recently been the most popular research topics. For those newly developed services, identifying the object in the picture taken by the camera on the phone performs an extremely important role. So, many researches of identifying pictures have been published and most of them are based on the time consuming image recognition techniques. On the contrary, this paper introduces a very fast and effective method of identifying the objects on the photo making use of the sensor data obtained from the smart phone and electronic maps. Our method estimates the line of sight of the camera with the location and orientation information provided by the smart phone. Then it finds any element of the map which intersects the line of sight. By investigating those intersecting elements, our method identifies the objects on the photo.

참고문헌 (Reference)

1 김경중, "상황인지 휴대폰 기술개발 동향" 정보통신산업진흥원 (1280) : 2007

2 주재훈, "개인화 콘텐트 서비스 방법"

3 Mitchell, K, "uLearn : Facilitating Ubiquitous Learning Through Camera Equipped Mobile Phones" 2005

4 Mohring, M, "Video See Through Consumer Cell-Phones" 252-253, 2004

5 Kalkusch, M, "Structured Visual Markers for Indoor Pathfinding" 2002

6 Chen, D, "Streaming Mobile Augmented Reality on Mobile Phones" 181-182, 2009

7 Li, Y, "Showroom introduction using mobilephone based on scene image recognition" 1294-1297, 2009

8 Lim, J, "Scene Recognition with Camera Phonesfor Tourist Information Access" 100-103, 2007

9 Skrypnyk, I, "Scene Modelling, Recognition and Tracking with Invariant Image Features" 110-119, 2004

10 Lee, A, "Real-Time Camera Pose Estimation forAugmented Reality System Using aSquare Marker" 1-2, 2010

11 Hile, H, "Positioning and Orientation in Indoor Environments Using Camera Phones" 28 (28): 32-39, 2008

12 Bruns, E, "Mobile Phone-Enabled Museum Guidancewith Adaptive Classification" 28 (28): 98-102, 2008

13 Han, E, "Mobile Education through Camera-Equipped Mobile Phones" 1656-1661, 2007

14 Paucher, R, "Location-Based Augmented Reality on Mobile Phones" 9-16, 2010

15 Yim, J, "Introducing a Decision Treebased Indoor Positioning Technique" 34 (34): 1296-1302, 2008

16 Mulloni, A, "Indoor Positioning and Navigation with Camera Phones" 22-31, 2009

17 Cipolla, R, "Imagebased Localization" 22-29, 2004

18 Abe, T, "Image-Identification Methods for Camera-Equipped Mobile Phones" 372-376, 2007

19 Vandenhouten, R, "Identification and tracking of goods with the mobile phone" 25-29, 2007

20 Rosten, E, "Fusing Points and Lines for High Performance Tracking" 2 : 1508-1515, 2005

21 Wagner, D, "First Steps Towards Handheld Augmented Reality" 21-23, 2003

22 Noh, H, "Exploiting Indoor Location and Mobile Information for Context-Awareness Service" 2011

23 Schmalstieg, D, "Experiences with Handheld Augmented Reality" 3-8, 2007

24 Oe, M, "Estimating Camera Position and Posture by Using Feature Landmark Database" 171-181, 2005

25 Bruns, E, "Enabling Mobile Phones To Support Large-Scale Museum Guidance" 14 (14): 16-25, 2007

26 Vacchetti, L, "Combining Edge and Texture Informationfor Real-Time Accurate 3d CameraTracking" 48-57, 2004

27 Abe, N, "Clickable Real World : Interaction with Real-World Landmarks Using Mobile Phone Camera" 914-917, 2010

28 Yeo, C, "Click4BuildingID@NTU : Click for Building Identification with GPS-enabled Camera Cell Phone" 1059-1062, 2007

29 Naimark, L, "Circular Data Matrix Fiducial System and Robust Image Processing for a Wearable Vision Inertial Self-Tracker" 27-, 2002

30 Sato, J, "Change Detection in Streetscapes from GPS Coordinated Omni-Directional Image Sequences" 4 : 935-938, 2006