Toward augmenting everything: Detecting and tracking geometrical features on planar objects

2011 10th IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2011

Volumn , Issue , 2011, Pages 17-25

  Uchiyama, Hideaki ^a   Marchand, Eric ^a,b  

^a INRIA   (France)

^b UNIVERSITÉ DE RENNES 1   (France)

Author keywords

H.5.1 INFORMATION INTERFACES AND PRESENTATION (e.g., HCI) : Multimedia Information Systems Artificial, augmented, and virtual realities; I.4.8 IMAGE PROCESSING AND COMPUTER VISION : Scene Analysis Tracking

Indexed keywords

FIDUCIAL MARKER; GEOMETRICAL FEATURES; H.5.1 [INFORMATION INTERFACES AND PRESENTATION (E.G. , HCI)]: MULTIMEDIA INFORMATION SYSTEMS-ARTIFICIAL , AUGMENTED , AND VIRTUAL REALITIES; I.4.8 [IMAGE PROCESSING AND COMPUTER VISION]; KEYPOINTS;

AUGMENTED REALITY; STABILITY CRITERIA; VIRTUAL REALITY;

COMPUTER VISION;

EID: 84055199670     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISMAR.2011.6092366     Document Type: Conference Paper

References (31)

1. http://opencv.willowgarage.com.
2. M. Agrawal, K. Konolige, and M. R. Bias. CenSurE: Center surround extremas for realtime feature detection and matching. In ECCV, pages 102-115,2008.
3. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool. Speeded-up robust features (SURF). CVIU, 110:346-359, 2008.
4. M. Calonder, V. Lepetit, C. Strecha, and P. Fua. BRIEF: Binary robust independent elementary features. In ECCV, pages 778-792, 2010.
5. V. Chandrasekhar, G. Takacs, D. M. Chen, S. S. Tsai, R. Grzeszczuk, and B. Girod. CHoG: Compressed histogram of gradients a low bitrate feature descriptor. In CVPR, pages 2504-2511, 2009.
6. O. Chum and J. Matas. Geometric hashing with local affine frames. In CVPR, pages 879-884, 2006.
7. R. T. Collins and W. Ge. CSDD features: Center-surround distribution distance for feature extraction and matching. In ECCV, pages 140-153, 2008.
8. A. Dame and E. Marchand. Accurate real-time tracking using mutual information. In ISMAR, pages 47-56, 2010.
9. M. A. Fischler and R. C. Bolles. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. C. of ACM, 24:381-395, 1981.
10. P.-E. Forssén and D. Lowe. Shape descriptors for maximally stable extremal regions. In CVPR, pages 778-792, 2007.
11. S. Gauglitz, T. Höllerer, and M. Turk. Evaluation of interest point detectors and feature descriptors for visual tracking. IJCV, 2011.
12. C. Harris and M. Stephens. A combined corner and edge detector. In AVC, pages 147-151, 1988.
13. H. Kato and M. Billinghurst. Marker tracking and HMD calibration for a video-based augmented reality conferencing system. In IWAR, pages 85-94, 1999.
14. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60:91-110, 2004.
15. E. Mair, G. D. Hager, D. Burschka, M. Suppa, and G. Hirzinger. Adaptive and generic corner detection based on the accelerated segment test. In ECCV, pages 183-196, 2010.
16. K. Mikolajczyk and C. Schmid. Scale & affine invariant interest point detectors. IJCV, 60:63-86, 2004.
17. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. TPAMI, 27:1615-1630, 2005. (Pubitemid 41555406)
18. J. Moraleda and J. J. Hull. Toward massive scalability in image matching. In ICPR, pages 3424-3427, 2010.
19. P. Moreels and P. Perona. Evaluation of features detectors and descriptors based on 3D objects. IJCV, 73:263-284, 2007. (Pubitemid 46227275)
20. M. Muja and D. G. Lowe. Fast approximate nearest neighbors with automatic algorithm configuration. In VISSAPP, pages 331-340, 2009.
21. T. Nakai, K. Kise, and M. Iwamura. Use of affine invariants in locally likely arrangement hashing for camera-based document image retrieval. In DAS, pages 541-552, 2006.
22. M. Ozuysal, M. Calonder, V. Lepetit, and P. Fua. Fast keypoint recognition using random ferns. TPAMI, 32:448-461, 2010.
23. Y. Park, V. Lepetit, and W. Woo. ESM-Blur: Handling & rendering blur in 3D tracking and augmentation. In ISMAR, pages 163-166, 2009.
24. J. Pilet and H. Saito. Virtually augmenting hundreds of real pictures: An approach based on learning, retrieval, and tracking. In IEEEVR, pages 71-78, 2010.
25. E. Rosten, R. Porter, and T. Drummond. Faster and better: A machine learning approach to corner detection. TPAMI, 32:105-119, 2010.
26. C. Schmid, R. Mohr, and C. Bauckhage. Evaluation of interest point detectors. IJCV, 37:151-172, 2000.
27. J. Shi and C. Tomasi. Good features to track. In CVPR, pages 593-600, 1994.
28. G. Takacs, V. Chandrasekhar, S. S. Tsai, D. M. Chen, R. Grzeszczuk, and B. Girod. Unified real-time tracking and recognition with rotation-invariant fast features. In CVPR, pages 934-941, 2010.
29. H. Uchiyama and H. Saito. Random dot markers. In IEEEVR, pages 35-38, 2011.
30. H. Uchiyama, H. Saito, M. Servierés, and G. Moreau. Camera tracking by online learning of keypoint arrangements using LLAH in augmented reality applications. VR, 2010.
31. D. Wagner, G. Reitmayr, A. Mulloni, T. Drummond, and D. Schmalstieg. Pose tracking from natural features on mobile phones. In ISMAR, pages 125-134, 2008.