Computer vision for mobile augmented reality

Mobile Cloud Visual Media Computing: From Interaction to Service

Volumn , Issue , 2015, Pages 3-42

  Turk, Matthew ^a   Fragoso, Victor ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b WEST VIRGINIA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUGMENTED REALITY; ENERGY EFFICIENCY; INDOOR POSITIONING SYSTEMS; OBJECT RECOGNITION;

COMPUTATIONAL RESOURCES; INDOOR LOCALIZATION; MOBILE AUGMENTED REALITY; OBJECT AND SCENES; PRECISE ALIGNMENTS; TRADITIONAL COMPUTERS; USER INTERACTION; VISION CAPABILITY;

COMPUTER VISION;

EID: 84956770225     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-319-24702-1_1     Document Type: Chapter

References (52)

1. Arthur, D., Vassilvitskii, S.: K-means++: the advantages of careful seeding. In: Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA’07, pp. 1027–1035. Society for Industrial and Applied Mathematics, New Orleans, Louisiana (2007)
2. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
3. Beis, J.S., Lowe, D.G.: Shape indexing using approximate nearest-neighbour search in highdimensional spaces. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (1997)
4. Benhimane, S., Malis, E.: Real-time image-based tracking of planes using efficient secondorder minimization. Proc. IEEE Int. Conf. Intell. Robot. Syst. (IROS 2004) 1, 943–948 (2004)
5. Bissacco, A., Cummins, M., Netzer, Y., Neven, H.: Photoocr: reading text in uncontrolled conditions. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV) (2013)
6. Brahmachari, A.S., Sarkar, S.: Blogs: balanced local and global search for non-degenerate two view epipolar geometry. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1685–1692 (2009)
7. Brown, M., Winder, S., Szeliski, R.: In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2005)
8. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal.Mach. Intell. 8(6), 679–698 (1986)
9. Castillo, E., Hadi, A.S., Balakrishnan, N., Sarabia, J.M.: Extreme Value and Related Models with Applications in Engineering and Science. Wiley, Hoboken (2005)
10. Cheng, C.-C., Peng, G.-J., Hwang, W.-L.: Subband weighting with pixel connectivity for 3-d wavelet coding. IEEE Trans. Image Process. 18(1), 52–62 (2009)
11. Chum, O., Matas, J.: Matching with prosac—progressive sample consensus. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2005)
12. Coles, S.: An Introduction to Statistical Modeling of Extreme Values. Springer, Berlin (2001)
13. Crandall, D., Owens, A., Snavely, N., Huttenlocher, D.: SfM with MRFs: discrete-continuous optimization for large-scale reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 35(12), 12 (2013)
14. Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2010)
15. Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)
16. Fragoso, V., Turk, M.: SWIGS: a swift guided sampling method. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2013)
17. Fragoso, V., Gauglitz, S., Zamora, S., Kleban, J., Turk, M.: TranslatAR: a mobile augmented reality translator. In: Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV’11) (2011)
18. Fragoso, V., Sen, P., Rodriguez, S., Turk, M.: EVSAC: accelerating hypotheses generation by modeling matching scores with extreme value theory. In: Proceedings of IEEE International Conference on Computer Vision (ICCV) (2013)
19. Gao, J., Yang, J.: An adaptive algorithm for text detection from natural scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2001)
20. Gauglitz, S., Höllerer, T., Turk, M.: Evaluation of interest point detectors and feature descriptors for visual tracking. Int. J. Comput. Vis. 94(3), 335–360 (2011)
21. Gauglitz, S., Sweeney, C., Ventura, J., Turk, M., Höllerer, T.: Live tracking and mapping from both general and rotation-only camera motion. In: Proceedings of the 11th IEEE International Symposium onMixed andAugmented Reality (ISMAR’12), pp. 13–22. Atlanta, Georgia (2012)
22. Goshen, L., Shimshoni, I.: Balanced exploration and exploitation model search for efficient epipolar geometry estimation. IEEE Trans. PatternAnal. Mach. Intell. 30(7), 1230–1242 (2008)
23. Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000). ISBN 0521623049
24. Jaderberg, M., Vedaldi, A., Zisserman, A.: Deep features for text spotting. In: Computer Vision ECCV 2014. Lecture Notes in Computer Science, vol. 8692, pp. 512–528. Springer International Publishing, Berlin (2014)
25. Kato, H., Billinghurst, M.: Marker tracking and hmd calibration for a video-based augmented reality conferencing system. In: Proceedings of the 2nd IEEE andACMInternationalWorkshop on Augmented Reality, 1999 (IWAR’99), pp. 85–94 (1999)
26. Klein, G., Murray, D.: Parallel tracking and mapping for small ARworkspaces. In: Proceedings of the Sixth IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR’07), Nara, Japan (2007)
27. Kneip, L., Li, H., Seo, Y.: UPnP: an optimal O(n) solution to the absolute pose problem with universal applicability. In: Computer Vision ECCV 2014. Lecture Notes in Computer Science, vol. 8689, pp. 127–142. Springer International Publishing, Berlin (2014)
28. Lee, C.W., Jung, K., Kim, H.J.: Automatic text detection and removal in video sequences. Pattern Recognit. Lett. 24(15), 2607–2623 (2003)
29. Lee, C.-Y., Bhardwaj, A., Di, W., Jagadeesh, V., Piramuthu, R.: Region-based discriminative feature pooling for scene text recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014)
30. Lepetit, V., Moreno-Noguer, F., Fua, P.: EPnP: an accurate O(n) solution to the PnP problem. Int. J. Comput. Vis. 81(2), 155–166 (2009)
31. Levenberg, K.: A method for the solution of certain non-linear problems in least squares. Q. J. Appl. Math. II(2), 164–168 (1944)
32. Levenshtein, I.V.: Binary codes capable of correcting deletions, insertions, and reversals. Cybern. Control Theory 10(8), 707–710 (1966)
33. Liu, Y., Goto, S., Ikenaga, T.: A contour-based robust algorithm for text detection in color images. IEICE—Trans. Inf. Syst. E89–D (3), 1221–1230 (2006)
34. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
35. Lucas, S.M.: LCDAR 2005 text locating competition results. Proc. IEEE Conf. Doc. Anal. Recognit. 1, 80–84 (2005)
36. Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
37. Neumann, L., Matas, J.: Real-time scene text localization and recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2012)
38. Neumann, L., Matas, J.: Scene text localization and recognition with oriented stroke detection. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV) (2013)
39. Park, A., Jung, K.:Automaticword detection system for document image usingmobile devices. In:Human-Computer Interaction. Interaction Platforms andTechniques. LectureNotes in Computer Science, vol. 4551, pp. 438–444. Springer, Berlin (2007)
40. Paucher, P., Turk, M.: Location-based augmented reality on mobile phones. In: Proceedings of IEEE Conference on ComputerVision and Pattern RecognitionWorkshops (CVPRWorkshops) (2010)
41. Petter, M., Fragoso, V., Turk, M., Baur, C.: Automatic text detection for mobile augmented reality translation. In: Proceedings of IEEE International Conference on Computer Vision Workshops (ICCV Workshops) (2011)
42. Raguram, R., Frahm, J.-M., Pollefeys, M.: A comparative analysis of ransac techniques leading to adaptive real-time random sample consensus. In: Computer Vision ECCV 2008. Springer, Berlin (2008)
43. Rousseeuw, P.J.: Least median of squares regression. J. Am. Stat. Assoc. 79(388), 871–880 (1984)
44. Scheirer, W. J., Rocha, A., Micheals, R. J., Boult, T. E.:Meta-eecognition: the theory and practice of recognition score analysis. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1689–1695 (2011)
45. Smith, R.: An overview of the tesseract ocr engine. In: Proceedings of the Ninth International Conference on Document Analysis and Recognition, ICDAR’07, vol. 2, pp. 629–633. IEEE Computer Society (2007)
46. Sweeney, C., Fragoso, V., Hllerer, T., Turk, M.: gDLS: a scalable solution to the generalized pose and scale problem. In: ComputerVision ECCV 2014. LectureNotes in Computer Science, vol. 8692, pp. 16–31. Springer International Publishing, Berlin (2014)
47. Tordoff, B.J., Murray, D.W.: Guided-MLESAC: faster image transform estimation by using matching priors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1523–1535 (2005)
48. Torr, P.H.S., Zisserman, A.: MLESAC: a new robust estimator with application to estimating image geometry. Comput. Vis. Image Underst. 78(1), 138–156 (2000)
49. Wagner, D., Schmalstieg, D.: Artoolkitplus for pose tracking onmobile devices. In: Proceedings of the 12th Computer Vision Winter Workshop (CVWW’07), pp. 139–146 (2007)
50. Wagner, D., Mulloni, A., Langlotz, T., Schmalstieg, D.: Real-time panoramic mapping and tracking on mobile phones. In: IEEE Virtual Reality Conference (VR). IEEE, pp. 211–218 (2010)
51. Ye, Q., Gao, W., Wang, W., Zeng, W.: A robust text detection algorithm in images and video frames. Proc. IEEE Int. Conf. Inf. Commun. Signal Process. 2, 802–806 (2003)
52. Ye, Q., Huang, Q., Gao, W., Zhao, D.: Fast and robust text detection in images and video frames. Image Vis. Comput. 23(6), 565–576 (2005)