• No results found

Semi-interactive construction of 3D event logs for scene investigation - Bibliography

N/A
N/A
Protected

Academic year: 2021

Share "Semi-interactive construction of 3D event logs for scene investigation - Bibliography"

Copied!
13
0
0

Bezig met laden.... (Bekijk nu de volledige tekst)

Hele tekst

(1)

UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl)

Semi-interactive construction of 3D event logs for scene investigation

Dang, T.K.

Publication date

2013

Link to publication

Citation for published version (APA):

Dang, T. K. (2013). Semi-interactive construction of 3D event logs for scene investigation.

General rights

It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).

Disclaimer/Complaints regulations

If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.

(2)

[1] G. Sparr A. Heyden, R. Berthilsson. An iterative factorization method for projective structure and motion from image sequences. Image and Vision Computing, 17(13):981–991, 1999.

[2] Henrik Aanæs, Anders Lindbjerg Dahl, and Kim Steenstrup Pedersen. Interesting interest points - a comparative study of interest point performance on a unique data set. International Journal

of Computer Vision, 97(1):18–35, 2012.

[3] Golnaz Abdollahian, Cuneyt M. Taskiran, Zygmunt Pizlo, and Edward J. Delp. Camera motion-based analysis of user generated video. IEEE Transactions on Multimedia, 12(1):28–41, 2010.

[4] Aseem Agarwala, Mira Dontcheva, Maneesh Agrawala, Steven Drucker, Alex Colburn, Brian Curless, David Salesin, and Michael Cohen. Interactive digital photomontage. In SIGGRAPH

’04: ACM SIGGRAPH 2004 Papers, pages 294–302, 2004.

[5] Sameer Agarwala, Yasutaka Furukawaa, Noah Snavely, Ian Simonb, Brian Curless, Steven M. Seitz, and Richard Szeliski. Building rome in a day. Communications of the ACM, 54(10):105– 112, 2011.

[6] N. Aggarwal and W. C. Karl. Line detection in images through regularized hough transform. In

IEEE International Conference on Image Processing, volume 3, pages 873–876, 2000.

[7] Kiyoharu Aizawa. Digitizing personal experiences: Capture and retrieval of life log. In MMM

’05: Proceedings of the 11th International Multimedia Modelling Conference, pages 10–15,

2005.

[8] Albert Albiol, Luis Torrest, and Edward J. Delpt. The indexing of persons in news sequences using audio-visual data. In IEEE International Conference on Acoustic, Speech, and Signal

processing, 2003.

[9] S. Avidan and A. Shashua. Threading fundamental matrices. IEEE Transactions on Pattern

Analysis and Machine Intelligence, 23(1):73–77, 2001.

(3)

[10] P. Bao and D. Gourlay. A framework for remote rendering of 3-D scenes on limited mobile devices. IEEE Transactions on Multimedia, 8(2):382–389, 2006.

[11] A. Baumberg. Reliable feature matching across widely separated views. In Conference on

Computer Vision and Pattern Recognition, pages 774–781, 2000.

[12] H. Bay, T. Tuytelaars, and L. Van Gool. SURF: Speeded up robust features. In European

Conference on Computer Vision, Lecture Notes in Computer Science, pages 404–417, 2006.

[13] Herbert Baya, Andreas Essa, Tinne Tuytelaars, and Luc Van Gool. Speeded-up robust features (SURF). Computer Vision Image Understanding, 110(3):346–359, 2008.

[14] P. A. Beardsley, P. H. S. Torr, and A. Zisserman. 3D model acquisition from extended image sequences. In European Conference on Computer Vision, volume 2, pages 683–695, 1996.

[15] J. S. Beis and D. G. Lowe. Shape indexing using approximate nearest-neighbor search in high-dimensional spaces. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1000–1006, 1997.

[16] J. R. Bergen, P. Anandan, K. J. Hanna, and R. Hingorani. Hierarchical model-based motion estimation. In European Conference on Computer Vision, pages 237–252, 1992.

[17] Jurrien Bijhold, Arnout Ruifrok, Michael Jessen, Zeno Geradts, Sabine Ehrhardt, and Ivo Al-berink. Forensic audio and visual evidence 2004-2007: A review. 15th INTERPOL Forensic

Science Symposium, 2007.

[18] J. S. De Bonet and P. Viola. Poxels: Probabilistic voxelized volume reconstruction. In

Interna-tional Conference on of Computer Vision, pages 418–425, 1999.

[19] J. Y. Bouguet. Camera calibration toolbox for matlab. http://www.vision.caltech. edu/bouguetj/calib{\_}doc/.

[20] M. Brown and D. G. Lowe. Automatic panoramic image stitching using invariant features.

In-ternational Journal of Computer Vision, 74(1):59–73, 2007.

[21] Vannevar Bush. As we may think. The Atlantic, 1945.

[22] J. Canny. A computational approach to edge detection. IEEE Transactions on Pattern Analysis

and Machine Intelligence, 8(6):769–698, 1986.

[23] M. Chandraker, S. Agarwal, F. Kahl, D. Nister, and D. Kriegman. Autocalibration via rank-constrained estimation of the absolute quadric. In IEEE Computer Vision and Pattern

Recogni-tion, pages 1–8, 2007.

[24] M. Ming-Yuen Chang and K. Hong Wong. Model reconstruction and pose acquisition using extended Lowes method. IEEE Transactions on Multimedia, 7(2):253–260, 2005.

[25] I. Cheng and P. Boulanger. Adaptive online transmission of 3-D TexMesh using scale-space and visual perception analysis. IEEE Transactions on Multimedia, 8(3):550–563, 2006.

[26] O. Chum, T. Werner, and J. Matas. Two-view geometry estimation unaffected by a dominant plane. In IEEE Conference on Computer Vision and Pattern Recognition, volume 1, pages 772– 779, 2005.

(4)

[27] Roberto Cipolla and Duncan Robertson. 3D models of architectural scenes from uncalibrated images and vanishing points. In International Conference on Image Analysis and Processing, pages 824–829, 1999.

[28] K. Cornelis, M. Pollefeys, and L. Van Gool. Lens distortion recovery for accurate sequential structure and motion recovery. In European Conference on Computer Vision, pages 186–200, 2002.

[29] K. Cornelis, F. Verbiest, and L. Van Gool. Drift detection and removal for sequential struc-ture from motion algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(10):1249–1259, 2004.

[30] Nico Cornelis, Bastian Leibe, Kurt Cornelis, and Luc Van Gool. 3D urban scene modeling integrating recognition and reconstruction. International Journal of Computer Vision, 78(2-3):121–141, 2008.

[31] Trung Kien Dang and Marcel Worring. Dealing with degenerate input in 3D modeling of indoor scenes using handheld cameras. In IEEE Conference on Multimedia and Expo, pages 108–111, 2007.

[32] Trung Kien Dang, Marcel Worring, and The Duy Bui. A semi-interactive panorama based 3D reconstruction framework for indoor scenes. Computer Vision and Image Understanding, 115:1516–1524, 2011.

[33] P. Daras, D. Zarpalas, D. Tzovaras, and M.G. Strintzis. Efficient 3-D model search and retrieval using generalized 3-D radon transforms. IEEE Transactions on Multimedia, 8(1):101–114, 2006.

[34] Paul E. Debevec, Camillo J. Taylor, and Jitendra Malik. Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach. In SIGGRAPH Annual

Con-ference on Computer Graphics and Interactive Techniques, pages 11–20, 1996.

[35] F. Devernay and O. Faugeras. Straight lines have to be straight: automatic calibration and re-moval of distortion from scenes of structured environments. Machine Vision and Applications, 13:14–24, 2001.

[36] Connor Dickie, Roel Vertegaal, David Fono, Changuk Sohn, Daniel Chen, Daniel Cheng, Jef-frey S Shell, and Omar Aoudeh. Augmenting and sharing memory with eyeblog. In CARPE’04:

Proceedings of the the 1st ACM workshop on Continuous archival and retrieval of personal experiences, pages 105–109, 2004.

[37] Aiden R. Doherty and Alan F. Smeaton. Automatically segmenting lifelog data into events. In WIAMIS ’08: Proceedings of the 2008 Ninth International Workshop on Image Analysis for

Multimedia Interactive Services, pages 20–23, 2008.

[38] Aiden R. Doherty, Alan F. Smeaton, Keansub Lee, and Daniel P. W. Ellis. Multimodal segmen-tation of lifelog data. In in Proc. RIAO 2007,Pittsburgh, 2007.

[39] Sabry El-Hakim, Emily Whiting, and Lorenzo Gonzo. 3D modeling with reusable and integrated building blocks. In The 7th Conference on Optical 3-D Measurement Techniques, pages 3–5, 2005.

[40] Isaac Esteban, Judith Dijk, and Frans C.A. Groen. Automatic 3d reconstruction of the urban landscape. In International Congress on Ultra Modern Telecomunications and Control Systems, 2010.

(5)

[41] Isaac Esteban, Leo Dorst, and Judith Dijk. Closed form solution for the scale ambiguity problem in monocular visual odometry. In International Conference on Intelligent Robotics and

Applica-tions, 2010.

[42] Dirk Farin, Wolfgang Effelsberg, and Peter H. N. de With. Floor-plan reconstruction from panoramic images. In ACM Multimedia, pages 823 – 826, 2007.

[43] O. Faugeras. Stratification of 3-D vision: projective, affine, and metric representations. Journal

of the Optical Society of America, 12(3):465–484, 1994.

[44] O. Faugeras, Q. T. Luong, and T. Papadopoulo. The Geometry of Multiple Images : The Laws

That Govern the Formation of Multiple Images of a Scene and Some of Their Applications. MIT

Press, 2001.

[45] M. A. Fischler and R. C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communication of the ACM, 24:381–395, 1981.

[46] A. Fitzgibbon and A. Zisserman. Automatic 3D model acquisition and generation of new images from video sequences. In European Signal Processing Conference, pages 1261–1269, 1998.

[47] L. A. Forbes and B. A. Draper. Inconsistencies in edge detector evaluation. In Computer Vision

and Pattern Recognition, volume 2, page 2398, 2000. no tensor, 2 views.

[48] J. M. Frahm and M. Pollefeys. RANSAC for (Quasi-)degenereate data (QDEGSAC). IEEE

Conference on Computer Vision and Pattern Recognition, 2006.

[49] J. H. Friedman, J. L. Bentley, and R. A. Finkel. An algorithm for finding best matches in loga-rithmic expected time. ACM Transactions on Mathematical Software, 3:209–226, 1977.

[50] E. Frontoni and P. Zingaretti. Visual feature group matching for autonomous robot localization. In 14th International Conference on Image Analysis and Processing, pages 197–204, 2007.

[51] Yasutaka Furukawa and Jean Ponce. Accurate, dense, and robust multiview stereopsis. IEEE

Transactions on Pattern Analysis and Machine Intelligence, 32(8):1362–1376, 2010.

[52] Jim Gemmell, Lyndsay Williams, Ken Wood, Roger Lueder, and Gordon Bell. Passive capture and ensuing issues for a personal lifetime store. In CARPE’04: Proceedings of the the 1st ACM

workshop on Continuous archival and retrieval of personal experiences, pages 48–55, 2004.

[53] J. M. Geusebroek, G. J. Burghouts, and A. W. M. Smeulders. The Amsterdam library of object images. International Journal of Computer Vision, 61(1):103–112, 2005.

[54] S. Gibson and T. Howard. Interactive reconstruction of virtual environments from photographs, with application to scene-of-crime analysis. In ACM symposium on Virtual reality software and

technology, pages 41–48, 2000.

[55] S. Gibson, R. J. Hubbold, J. Cook, and T. L. J. Howard. Interactive reconstruction of virtual environments from video sequences. Computers & Graphics, 27(2):293–301, 2003.

[56] Dan B. Goldman, Chris Gonterman, Brian Curless, David Salesin, and Steven M. Seitz. Video object annotation, navigation, and composition. In UIST ’08: Proceedings of the 21st annual

(6)

[57] Ralf Haeusler, Reinhard Klette, and Fay Huang. Monocular 3D reconstruction of objects based on cylindrical panoramas. In 3rd Pacific Rim Symposium on Advances in Image and Video

Technology, pages 60–70, 2008.

[58] M. Han and T. Kanade. A perspective factorization method for Euclidean reconstruction with uncalibrated cameras. Journal of Visualization and Computer Animation, 13(4):211–223, 2002.

[59] C. Harris and M. Stephens. A combined corner and edge detector. In Fourth Alvey Vision

Conference, pages 147–151, 1988.

[60] R. Hartley and S. B. Kang. Parameter-free radial distortion correction with center of distortion estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(8):1309–1321, 2007.

[61] R. Hartley and A. Zisserman. Multiple view geometry in computer vision – 2nd edition. Cam-bridge University Press, 2004.

[62] R. I. Hartley. Estimation of relative camera positions for uncalibrated cameras. Lecture Notes In

Computer Science, 588:579–587, 1992.

[63] R. I. Hartley. Cheirality. International Journal of Computer Vision, 26(1):41–61, 1998.

[64] R. I. Hartley. Theory and practice of projective rectification. International Journal of Computer

Vision, 35(2):115–127, 1999.

[65] R. I. Hartley and P. Sturm. Triangulation. Computer Vision and Image Understanding, 68:146– 157, 1998.

[66] Tal Hassner, Viki Mayzels, and Lihi Zelnik-Manor. On sifts and their scales. In IEEE Conf. on

Computer Vision and Pattern Recognition, 2012.

[67] A. Heyden and K. ˚Astr¨om. Minimal conditions on intrinsic parameters for euclidean reconstruc-tion. In Asian Conference on Computer Vision, 1998.

[68] S. Heymann, K. M¨uller, and A. Smolic. SIFT implementation and optimization for general-purpose GPU. In International Conference in Central Europe on Computer Graphics, pages 1–6, 2007.

[69] H. C. Longuet Higgins. A computer algorithm for reconstructing a scene from two projections.

Nature, 1981.

[70] A. Hilton, J. Illingworth A. J. Stoddart, and T. Windeatt. Marching triangle: Range image fusion for complex object modeling. In International Conference On Image Processing, pages 381–384, 1996.

[71] P. V. C. Hough. Machine analysis of bubble chamber pictures. In International Conference on

High Energy Accelerators and Instrumentation, 1959.

[72] T. L. J. Howard, A. D. Murta, and S. Gibson. Virtual environments for scene of crime recon-struction and analysis. In SPIE – Visual Data Exploration and Analysis VII, volume 3960, pages 1–8, 2000.

[73] C. Schmid K. Mikolajczyk. A performance evaluation of local descriptors. In Conference on

(7)

[74] F. Kahl, R. I. Hartley, and K. ˚Astr¨om. Critical configurations for n-view projective reconstruction. In Computer Vision and Pattern Recognition, volume 2, 2001.

[75] Hyung Woo Kang and Sung Yong Shin. Tour into the video: image-based navigation scheme for video sequences of dynamic scenes. In VRST ’02: Proceedings of the ACM symposium on

Virtual reality software and technology, pages 73–80, 2002.

[76] N. Karlsson, E. D. Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M. E. Munich. The vSLAM algorithm for robust localization and mapping. In IEEE International Conference on

Robotics and Automation, pages 24–29, 2005.

[77] Y. Ke and R. Sukthankar. PCA-SIFT: A more distinctive representation for local image descrip-tors. In Conference on Computer Vision and Pattern Recognition, volume 1, pages 511–517, 2004.

[78] C. Kim, K. M. Lee, B. T. Choi, and S. U. Lee. A dense stereo matching using two-pass dy-namic programming with generalized ground control points. In Computer Vision and Pattern

Recognition, volume 2, pages 1075–1082, 2005.

[79] Kihwan Kim, Irfan Essa, and Gregory D. Abowd. Interactive mosaic generation for video nav-igation. In MULTIMEDIA ’06: Proceedings of the 14th annual ACM international conference

on Multimedia, pages 655–658, 2006.

[80] Wonjun Kim and Changick Kim. An efficient correction method of wide-angle lens distortion for surveillance systems. In IEEE International Symposium on Circuits and Systems, pages 3206–3209, 2009.

[81] V. Kolmogorov and R. Zabih. Multi-camera scene reconstruction via graph cuts. In European

Conference on Computer Vision, pages 82–96, 2002.

[82] Bernhard Korte and Jens Vygen. Combinatorial Optimization: Theory and Algorithms – 3rd

edition. Algorithms and Combinatorics. Springer, 2005.

[83] Y. Kunii and H. Chikatsu. Efficient line matching by image sequential analysis for urban area modeling. International Society for Photogrammetry and Remote Sensing, page 221, 2004.

[84] R. I. Hartley L. de Agapito and E. Hayman. Linear calibration of rotating and zooming camera. In IEEE conference on Computer Vision and Pattern Recognition, pages 15–25, 1999.

[85] Dong-Jun Lan, Yu-Fei Ma, and Hong-Jiang Zhang. A novel motion-based representation for video mining. In International Conference on Multimedia and Expo, volume 3, pages 469–472, 2003.

[86] S. Lazebnik, C. Schmid, and J. Ponce. Sparse texture representation using affine-invariant neigh-borhoods. In International Conference on Computer Vision and Pattern Recognition, volume 2, pages 319–324, 2003.

[87] H. P. A. Lensch, J. Kautz, and M. Goesele. Image-based reconstruction of spatial appearance and geometric detail. ACM Transactions on Graphics, 22(2), 2003.

[88] Yin Li, Heung-Yeung Shum, Chi-Keung Tang, and Richard Szeliski. Stereo reconstruction from multiperspective panoramas. IEEE Transaction on Pattern Analysis and Machine Intelligence, 26(1):45–62, 2004.

(8)

[89] W. E. Lorensen and H. E. Cline. Marching cubes: A high resolution 3D surface reconstruc-tion algorithm. In 14th annual conference on computer graphics and interactive techniques, volume 21, pages 381–384, 1987.

[90] M. I.A. Lourakis and A. A. Argyros. The design and implementation of a generic sparse bundle adjustment software package based on the Levenberg-Marquardt algorithm. Technical Report 340, Institute of Computer Science - FORTH, Heraklion, Crete, Greece, 2004.

[91] M.I. A. Lourakis and A.A. Argyros. Sba: A software package for generic sparse bundle adjust-ment. ACM Trans. Math. Software, 36(1):1–30, 2009.

[92] D. G. Lowe. Object recognition from local scale-invariant features. In International Conference

on Computer Vision, volume 2, pages 1150–1157, 1999.

[93] D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of

Computer Vision, 60(2):91–110, 2004.

[94] L. Lucchese. Geometric calibration of digital cameras through multi-view rectification. Image

and Vision Computing, 23:517–539, 2005.

[95] Q. T. Luong and O. Faugeras. The fundamental matrix: Theory, algorithms, and stability analy-sis. International Journal of Computer Vision, 17(1):43–76, 1996.

[96] Q. T. Luong and T. Vieville. Canonical representations for the geometries of multiple projective views. Computer Vision and Image Understanding, 64(2):193–229, 1996.

[97] Yu-Fei Ma, Lie Lu, Hong-Jiang Zhang, and Mingjing Li. A user attention model for video summarization. In ACM Multimedia, pages 533–542, 2003.

[98] S. Mahamud, M. Hebert, Y. Omori, and J. Ponce. Provably-convergent iterative methods for pro-jective structure from motion. In IEEE Conference on Computer Vision and Pattern Recognition, volume 1, pages 1018–1025, 2001.

[99] J. Matas, O. Chum, M. Urban, and T. Pajdla. Robust wide-baseline stereo from maximally stable extremal regions. Image and Vision Computing, 22(10):761–767, 2004.

[100] Tao Mei, Xian-Sheng Hua, He-Qin Zhou, and Shipeng Li. Modeling and mining of users’ capture intention for home video. IEEE Transactions on Multimedia, 9(1), 2007.

[101] O. Le Meur, D. Thoreau, P. Le Callet, and D. Barba. A spatial-temporal model of the selective human visual attention. In International Conference on Image Processing, volume 3, pages 1188–1191, 2005.

[102] K. Mikolajczyk and C. Schmid. Indexing based on scale invariant interest points. In International

Conference on Computer Vision, volume 1, pages 525–531, 2001.

[103] K. Mikolajczyk and C. Schmid. Scale & affine invariant interest point detectors. International

Journal of Computer Vision, 60(1):63–86, 2004.

[104] K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE Transaction

(9)

[105] K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool. A comparison of affine region detectors. International Journal of Computer

Vision, 65(1):43–72, 2005.

[106] K. Murakami and T. Naruse. High speed line detection by hough transform in local area. In

IEEE International Conference on Pattern Recognition, volume 3, pages 467–470, 2000.

[107] Chong-Wah Ngo, Ting-Chuen Pong, and HongJiang Zhang. Motion-based video representation for scene change detection. International Journal of Computer Vision, 50(2):127–142, 2002.

[108] S. Maybank O. D. Faugeras, Q. Luong. Camera self-calibration: Theory and experiment.

Euro-pean Conference on Computer Vision, pages 321–334, 1992.

[109] D. Oram. Rectification for any epipolar geometry. In British Machine Vision Conference, 2001.

[110] U. Orguner and F. Gustafsson. Statistical characteristics of Harris corner detector. In IEEE

Workshop on Statistical Signal Processing, 2007.

[111] Patrick P´erez, Michel Gangnet, and Andrew Blake. Poisson image editing. ACM Trans. Graph., 22(3):313–318, 2003.

[112] R.L. Pires, P. de Smet, and I. Bruyland. Line extraction with the use of an automatic gradi-ent threshold technique and the hough transform. In IEEE International Conference on Image

Processing, volume 3, pages 909–912, 2000.

[113] M. Pollefeys. Self-calibration and metric 3D reconstruction from uncalibrated image sequences. PhD thesis, 1999.

[114] M. Pollefeys. Tutorial on 3D modeling from images, 2000.

http://www.esat.kuleuven.ac.be/∼pollefey/tutorial/.

[115] M. Pollefeys, R. Koch, and L. Van Gool. Selfcalibration and metric reconstruction in spite of varying and unknown intrinsic camera parameters. In IEEE International Conference on

Computer Vision, pages 90–95, 1998.

[116] M. Pollefeys, R. Koch, and L. Van Gool. A simple and efficient rectification method for general motion. In International Conference on Computer Vision, pages 496–501, 1999.

[117] M. Pollefeys, F. Verbiest, and L. Van Gool. Surviving dominant planes in uncalibrated structure and motion recovery. In European Conference on Computer Vision, pages 837–851, 2002.

[118] Marc Pollefeys, Luc J. Van Gool, Maarten Vergauwen, Kurt Cornelis, Frank Verbiest, and Jan Tops. Image-based 3D acquisition of archaeological heritage and applications. In Virtual Reality,

Archeology, and Cultural Heritage, pages 255–262, 2001.

[119] Marc Pollefeys, Reinhard Koch, and Luc Van Gool. Selfcalibration and metric reconstruction in spite of varying and unknown intrinsic camera parameters. International Journal of Computer

Vision, 32:7–25, 1999.

[120] Marc Pollefeys, David Nist´er, Jan-Michael Frahm, Amir Akbarzadeh, Philippos Mordohai, Brian Clipp, Christoph Engels, David Gallup, Seon Joo Kim, Paul Merrell, C. Salmi, Sudipta N. Sinha, B. Talton, Liang Wang, Qingxiong Yang, Henrik Stew´enius, Ruigang Yang, Greg Welch, and Herman Towles. Detailed real-time urban 3D reconstruction from video. International Journal

(10)

[121] Marc Pollefeys, Luc Van Gool, Maarten Vergauwen, Frank Verbiest, Kurt Cornelis, Jan Tops, and Reinhard Koch. Visual modeling with a hand-held camera. International Journal of Computer

Vision, 59:207–232, 2004.

[122] J. Ponce, K. McHenry, T. Papadopoulo, M. Teillaud, and B. Triggs. On the absolute quadratic complex and its application to autocalibration. In IEEE Conference on Computer Vision and

Pattern Recognition, volume 1, pages 780–787, 2005.

[123] Vivek Pradeep and Jongwoo Lim. Egomotion using assorted features. International Journal of

Computer Vision, 98(2):202–216, 2012.

[124] L. de Agapito R. I. Hartley, E. Hayman and I. Reid. Camera calibration and the search for infinity. In International Conference on Computer Vision, pages 510–517, 1999.

[125] J. Repko and M. Pollefeys. 3D model from extended uncalibrated video sequences: Addressing key-frame selection and projective drift. In International Conference on 3-D Digital Imaging

and Modeling, pages 150–157, 2005.

[126] Y. M. Ro, M. Kim, H. K. Kang, B. S. Manjunath, and J. Kim. MPEG-7 homogeneous texture descriptor. ETRI Journal, 32(2):41–51, 2001.

[127] Dirk Robinson and Peyman Milanfar. Fast local and global projection-based methods for affine motion estimation. Journal of Mathematical Imaging and Vision, 8(1):35–54, 2003.

[128] Edward Rosten and Tom Drummond. Machine learning for high-speed corner detection. In

European Conference on Computer Vision, volume 1, pages 430–443, May 2006.

[129] S. Roy, J. Meunier, and I. J. Cox. Cylindrical rectification to minimize epipolar distortion. In

Conference on Computer Vision and Pattern Recognition, page 393, 1997.

[130] Yong Rui, Anoop Gupta, and Alex Acero. Automatically extracting highlights for TV baseball program. In ACM Multimedia, pages 105–115, 2000.

[131] F. Schaffalitzky and A. Zisserman. Multi-view matching for unordered image sets. In European

Conference on Computer Vision, 2002.

[132] D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspon-dence algorithms. International Journal of Computer Vision, 47:7–42, 2002.

[133] E. Schechtman, Y. Caspi, and M. Irani. Space-time super-resolution. IEEE Transaction on

Pattern Analysis and Machine Intelligence, 27(4):531–545, 2005.

[134] C. Schmid, R. Mohr, and C. Bauckhage. Evaluation of interest point detectors. International

Journal of Computer Vision, 37(2):151–172, 2000.

[135] C. Schmid and A. Zisserman. The geometry and matching of lines and curves over multiple views. International Journal of Computer Vision, 40(3):199–233, 2000.

[136] S. M. Seitz, B. Curless, J. Diebel, D. Scharstein, and R. Szeliski. A comparison and evaluation of multi-view stereo reconstruction algorithms. In IEEE Computer Vision and Pattern Recognition, volume 1, pages 519–528, 2006.

(11)

[137] M. C. Shin, D. Goldgof, and K. W. Bowyer. An objective comparison methodology of edge detection algorithms using a structure from motion task. IEEE Conference on Computer Vision

and Pattern Recognition, pages 190–195, 1998.

[138] Heung-Yeung Shum, Mei Han, and Richard Szeliski. Interactive construction of 3D models from panoramic mosaics. In Computer Vision and Pattern Recognition, pages 427–433, 1998.

[139] Sudipta N. Sinha, Drew Steedly, Richard Szeliski, Maneesh Agrawala, and Marc Pollefeys. In-teractive 3D architectural modeling from unordered photo collections. ACM Transactions on

Graphics, 27(5):159, 2008.

[140] S. M. Smith and J. M. Brady. SUSAN – a new approach to low level image processing.

Interna-tional Journal of Computer Vision, 23(1):45–78, 1997.

[141] N. Snavely, S. M. Seitz, and R. Szeliski. Photo tourism: Exploring photo collections in 3D. ACM

Transactions on Graphics, 25(3):835–846, 2006.

[142] Noah Snavely, Steven M. Seitz, and Richard Szeliski. Modeling the world from internet photo collections. International Journal of Computer Vision, 80(2):189–210, 2008.

[143] C. G. M. Snoek and M. Worring. Concept-based video retrieval. Foundations and Trends in

Information Retrieval, 4(2):215–322, 2009.

[144] J. Stauder. Point light source estimation from two images and its limits. International Journal of

Computer Vision, 36(3):195–220, 2000.

[145] C. Steger. An unbiased detector of curvilinear structure. IEEE Transaction on Pattern Analysis

and Machine Intelligence, 20(2):113–125, 1998.

[146] P. Sturm. Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction. In Conference on Computer Vision and Pattern Recognition, pages 1100 – 1105, 1997.

[147] P. Sturm and B. Triggs. A factorization based algorithm for multi-image projective structure and motion. In European Conference on Computer Vision, pages 709–720, 1996.

[148] Z. Sun, V. Ramesh, , and A. M. Tekalp. Error characterization of the factorization method.

Computer Vision and Image Understanding, 82:110–137, 2001.

[149] Richard Szeliski. Image alignment and stitching: A tutorial. Foundations and Trends in

Com-puter Graphics and Vision, 2(1):1, 2006.

[150] Datchakorn Tancharoen, Toshihiko Yamasaki, and Kiyoharu Aizawa. Practical experience recording and indexing of life log video. In CARPE ’05: Proceedings of the 2nd ACM workshop

on Continuous archival and retrieval of personal experiences, pages 61–66, 2005.

[151] C. Taylor and D. Kriegman. Structure and motion from line segments in multiple images. IEEE

Transaction on Pattern Analysis and Machine Intelligence, 17(11):1021–1032, 1995.

[152] Thorsten Thorm¨ahlen and Hans-Peter Seidel. 3D-modeling by ortho-image generation from image sequences. In ACM SIGGRAPH, pages 1–5, 2008.

[153] C. Tomasi and T. Kanade. Shape and motion from image streams under orthography: A factor-ization method. International Journal of Computer Vision, 9(2):137–154, 1992.

(12)

[154] P. Torr. An assessment of information criteria for motion model selection. In IEEE Conference

on Computer Vision and Pattern Recognition, pages 47–52, 1997.

[155] P. Torr, A. W. Fitzgibbon, and A. Zisserman. Maintaining multiple motion model hypotheses over many views to recover matching and structure. In Sixth International Conference on Computer

Vision, page 485, 1998.

[156] P. Torr, A. W. Fitzgibbon, and A. Zisserman. The problem of degeneracy in structure and motion recovery from uncalibrated image sequences. International Journal of Computer Vision, 32(1), 1999.

[157] T. Tuytelaars and K. Mikolajczyk. Local invariant feature detectors: A survey. Foundations and

Trends in Computer Graphics and Vision, 3(3):177–280, 2008.

[158] Tinne Tuytelaars and Luc Van Gool. Wide baseline stereo matching based on local, affinely invariant regions. In British Machine Vision Conference, 2000.

[159] T. Ueshiba and F. Tomita. Plane-based calibration algorithm for multi-camera system via fac-torization of homography matrices. In IEEE International Conference on Computer Vision, vol-ume 2, pages 966–973, 2003.

[160] Anton van den Hengel, Anthony Dick, Thorsten Thorm¨ahlen, Ben Ward, and Philip H. S. Torr. VideoTrace: rapid interactive scene modelling from video. ACM Transactions on Graphics, 26(3):86, 2007.

[161] L. Van Gool, T. Moons, and D. Ungureanu. Affine/photometric invariants for planar intensity patterns. In European Conference on Computer Vision, pages 642–651, 1996.

[162] V. Venkateswar and R. Chellappa R. Hierarchical stereo and motion correspondence using fea-ture groupings. International Journal of Computer Vision, 15(3):245–269, 1995.

[163] Q. Wang and S. You. Fast similarity search for high-dimensional dataset. In Eighth IEEE

International Symposium on Multimedia, 2006.

[164] Wang Wei, Gao Hui, Zhang Maojun, and Xiong ZhiHui. Multi-perspective panorama based on the improved pushbroom model. Workshop on Digital Media and its Application in Museum &

Heritage, pages 85–90, 2007.

[165] Y. Wei and L. Quan. Asymmetrical occlusion handling using graph cut for multi-view stereo. In

IEEE Conference on Computer Vision and Pattern Recognition, volume 2, pages 902–909, 2005.

[166] M. Wilczkowiak, P.F. Sturm, and E. Boyer. Using geometric constraints through parallelepipeds for calibration and 3D modeling. Pattern Analysis and Machine Intelligence, 27(2):194–207, 2005.

[167] Changchang Wu. Visualsfm : A visual structure from motion system. http://www.cs. washington.edu/homes/ccwu/vsfm/.

[168] R. Zabih and J. Woodfill. Non-parametric local transforms for computing visual correspondence. In European Conference on Computer Vision, 1994.

[169] Z. Zhang. A flexible new technique for camera calibration. IEEE Transactions on Pattern

(13)

[170] Zhigang Zhu and Allen R. Hanson. LAMP: 3D layered, adaptive-resolution, and multi-perspective panorama – a new scene representation. Computer Vision Image Understanding, 96(3):294–326, 2004.

Referenties

GERELATEERDE DOCUMENTEN

To be specific the question looked at will be which claims in the American and Dutch climate change debate got the most attention and coverage in the elite national newspapers of

The study provides further evidence on the additional benefits of multiple micronutrient supplementation (including iron- folic acid) above iron-folic acid alone in women

The aim of this study was to determine whether selected students were more likely to complete their medical courses (on time) compared to students who were rejected during

1) Mortality rates should be positive. 2) The model should be consistent with historical data. 3) Long-term dynamics under the model should be biologically reasonable. 4)

Adding this stochastic process to a stochastic country population mortality model leads to stochastic portfolio specific mortality rates, measured in insured amounts. The

Stochastic processes for the occurrence times, the reporting delay, the development process and the payments are fit to the historical individual data of the portfolio and used

Een Gegarandeerde Annuiteit Optie (GAO) is een optie die een polishouder het recht biedt om het op de pensioendatum opgebouwde kapitaal om te zetten naar een levenslange

Voor heel complexe swaprente-afhankelijke embedded opties waarvan de prijzen middels Monte Carlo simulatie bepaald moeten worden, kan de rekentijd significant verminderd worden