Abstract
Augmented Reality is an emerging research field, that aims for the composition of real and virtual imagery, by means of a camera and display device. Spatial augmented reality employs data projectors to augment the real world. In this setting, traditional tracking methods fall short due to the interference caused by the projector. Recent works assume a calibration process to model the projector and assume continuity in movement of the object being tracked. In this paper we present a tracking-by-detection system that does not require such a procedure and makes use of natural features represented by SIFT descriptors. We evaluate a set of photometric invariants that have previously been shown to improve the performance of object recognition, added to the descriptor to reduce the influence of the projector. We evaluate the descriptors based on precision-recall under projector distortion and the total system based on its tracking performance. Results show tracking is significantly more precise using one of the invariants.
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Bimber, O., Raskar, R.: Spatial augmented reality - Merging Real and Virtual Worlds. A. K. Peters, Ltd., Natick (2005)
Audet, S., Okutomi, M., Tanaka, M.: Direct image alignment of projector-camera systems with planar surfaces. In: CVPR, pp. 303–310. IEEE (2010)
Audet, S., Okutomi, M., Tanaka, M.: Augmenting moving planar surfaces robustly with video projection and direct image alignment. Virtual Reality, 1–12, 10.1007/s10055-012-0210-9
van Gemert, J.C., Burghouts, G.J., Seinstra, F., Geusebroek, J.M.: Color invariant object recognition using entropic graphs. International Journal of Imaging Systems and Technology 16, 146–153 (2006)
Burghouts, G.J., Geusebroek, J.M.: Performance evaluation of local colour invariants. Computer Vision and Image Understanding 113, 48–62 (2009)
Audet, S., Cooperstock, J.R.: Shadow removal in front projection environments using object tracking. In: Projector-Camera Systems, pp. 1–8 (2007)
Majumder, A., Brown, M.S.: Practical Multi-projector Display Design. A. K. Peters, Ltd., Natick (2007)
Zhang, L., Nayar, S.: Projection defocus analysis for scene capture and image display. ACM Transactions on Graphics 25, 907–915 (2006)
Oyamada, Y., Saito, H.: Blind deconvolution based projector defocus removing with uncalibrated projector-camera pair. In: IEEE International Workshop on Projector-Camera Systems, PROCAMS (2009)
Grossberg, M.D., Peri, H., Nayar, S.K., Belhumeur, P.N.: Making one object look like another: Controlling appearance using a projector-camera system. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 452–459 (2004)
Johnson, T., Fuchs, H.: Real-time projector tracking on complex geometry using ordinary imagery. In: Projector-Camera Systems, p. 1 (2007)
Baker, S., Datta, A., Kanade, T.: Parameterizing homographies. Technical Report CMU-RI-TR-06-11, Robotics Institute, Pittsburgh, PA (2006)
Funt, B.V., Finlayson, G.D.: Color Constant Color Indexing. IEEE Transactions on Pattern Analysis and Machine Intelligence 17, 522–529 (1995)
Geusebroek, J.M., van den Boomgaard, R., Smeulders, A.W.M., Geerts, H.: Color invariance. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 1338–1350 (2001)
Geusebroek, J.-M., van den Boomgaard, R., Smeulders, A.W.M., Dev, A.: Color and Scale: The Spatial Structure of Color Images. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1842, pp. 331–341. Springer, Heidelberg (2000)
van de Weijer, J., Schmid, C.: Coloring Local Feature Extraction. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 334–348. Springer, Heidelberg (2006)
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of the International Conference on Computer Vision, ICCV 1999, vol. 2, pp. 1150–1157. IEEE Computer Society, Washington, DC (1999)
van de Sande, K.E.A., Gevers, T., Snoek, C.G.M.: Evaluating color descriptors for object and scene recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 1582–1596 (2010)
Geusebroek, J.-M., Dev, A., van den Boomgaard, R., Smeulders, A.W.M., Cornelissen, F., Geerts, H.: Color Invariant Edge Detection. In: Nielsen, M., Johansen, P., Fogh Olsen, O., Weickert, J. (eds.) Scale-Space 1999. LNCS, vol. 1682, pp. 459–464. Springer, Heidelberg (1999)
Koenderink, J.J.: The structure of images. Biological Cybernetics 50, 363–370 (1984)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 1615–1630 (2005)
Hartley, A., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press (2006)
Zisserman, A., Torr, P.H.S.: Robust parameterization and computation of the trifocal tensor. In: BMVC, Motion and Active Vision (1996)
Torr, P.H.S., Zisserman, A.: Robust computation and parametrization of multiple view relations. In: ICCV, pp. 727–732 (1998)
Schmid, C., Mohr, R., Bauckhage, C.: Evaluation of interest point detectors. International Journal of Computer Vision 37, 151–172 (2000)
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Kooi, T., de Sorbier, F., Saito, H. (2013). Colour Descriptors for Tracking in Spatial Augmented Reality. In: Park, JI., Kim, J. (eds) Computer Vision - ACCV 2012 Workshops. ACCV 2012. Lecture Notes in Computer Science, vol 7729. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37484-5_32
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DOI: https://doi.org/10.1007/978-3-642-37484-5_32
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