Abstract
We introduce, characterize and test a vision-based dead-reckoning system for wearable computing that allows to track the user’s trajectory in an unknown and non-instrumented environment by integrating the optical flow. Only a single inexpensive camera worn on the body is required, which may be reused for other purposes such as HCI. Result show that distance estimates are accurate (6-12%) while rotation tends to be underestimated. The accumulation of errors is compensated by identifying previously visited locations and “closing the loop”; it results in greatly enhanced accuracy. Opportunistic use of wireless signatures is used to identify similar locations. No a-priori knowledge of the environment such as map is needed, therefore the system is well-suited for wearable computing. We identify the limitations of this approach and suggest future improvements.
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References
Dey, A.K., Abowd, G.D.: Towards a better understanding of context and context awareness. Technical Report GITGVU-99-22, Georgia Tech. (1999)
Lukowicz, P., Junker, H., Staeger, M., von Bueren, T., Troester, G.: WearNET: A distributed multi-sensor system for context aware wearables. In: Borriello, G., Holmquist, L.E. (eds.) UbiComp 2002. LNCS, vol. 2498, pp. 361–370. Springer, Heidelberg (2002)
Simcock, T., Hillenbrand, P., Thomas, B.H.: Developing a location based tourist guide application. In: Johnson, C., Montague, P., Steketee, C. (eds.) Conferences in Research and Practice in Information Technology, Australian Computer Society, pp. 177–183 (2003)
Patterson, D.J., Liao, L., Fox, D., Kautz, H.: Inferring high-level behavior from low-level sensors. In: Goos, G., Hartmanis, J., van Leeuwen, J. (eds.) Proc. of the 5th Int. Conf. on Ubiquitous Computing, pp. 73–89. Springer, Heidelberg (2003)
Ashbrook, D., Starner, T.: Using gps to learn significant locations and predict movement across multiple users. Personal and Ubiquitous Computing 7(5), 275–286 (2004)
Haeberlen, A., Flannery, E., Ladd, A.M., Rudys, A., Wallach, D.S., Kavraki, L.E.: Practical robust localization over large-scale 802.11 wireless networks. In: Proc. of the 10th annual international conference on Mobile computing and networking, pp. 70–84. ACM Press, New York (2004)
Cavalieri, S.: A novel approach for localisation based on wi-fi. In: Proc. of the 3rd Int. Conf. on Industrial Informatics (INDIN), pp. 234–239 (2005)
Otsason, V., Varshavsky, A., La Marca, A., de Lara, E.: Accurate gsm indoor localization. In: Beigl, M., Intille, S.S., Rekimoto, J., Tokuda, H. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 141–158. Springer, Heidelberg (2005)
La Marca, A., Chawathe, Y., Consolvo, S., Hightower, J., Smith, I., Scott, J., Sohn, T., Howard, J., Hughes, J., Potter, F., Tabert, J., Powledge, P., Borriello, G., Schilit, B.: Place lab: Device positioning using radio beacons in the wild. In: Proc. of Pervasive Computing, pp. 116–133. Springer, Heidelberg (2005)
Hightower, J., Borriello, G.: Location systems for ubiquitous computing. IEEE Computer, 57–66 (2001)
Lee, S.W., Mase, K.: Activity and location recognition using wearable sensors. Pervasive Computing 1(3), 24–32 (2002)
Randell, C., Djiallis, C., Muller, H.: Personal position measurement using dead reckoning. In: ISWC 2003. Proc. of the 7th IEEE Int. Symposium on Wearable Computers, pp. 166–173. IEEE Computer Society, Los Alamitos (2003)
Schindler, G., Metzger, C., Starner, T.: A wearable interface for topological mapping and localization in indoor environments. In: Hazas, M., Krumm, J., Strang, T. (eds.) LoCA 2006. LNCS, vol. 3987, pp. 64–73. Springer, Heidelberg (2006)
Schilstra, C., Van Hateren, J.H.: Blowfly flight and optic flow I: thorax kinematics and flight dynamics. The Journal of Experimental Biology 202(11), 1481–1490 (1999)
Ellmore, T.M.: Human path integration by optic flow. Master’s thesis, Department of Psychology, The University of Arizona (2004)
Frenz, H., Bremmer, F., Lappe, M.: Discrimination of travel distance from ‘situated’ optic flow. Vision Research 43(20), 2173–2183 (2003)
Frenz, H., Lappe, M.: Absolute travel distance from optic flow. Vision Research 45(13), 1679–1692 (2005)
Srinivasan, M.V., Chahl, J.S., Zhang, S.W.: Robot navigation by visual dead-reckoning: inspiration from insects. International Journal of Pattern Recognition and Artificial Intelligence 11(1), 35–47 (1997)
De Souza, G.N., Kak, A.C.: Vision for mobile robot navigation: A survey. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(2), 237–267 (2002)
Kröse, B., Dev, A., Groen, F.: Heading direction of a mobile robot from the optical flow. Image and Vision Computing 18(5), 415–424 (2000)
Nagatani, K., Tachibana, S., Sofue, M., Tanaka, Y.: Improvement of odometry for omnidirectional vehicle using optical flow information. In: IEEE/RSJ Int. Conference on Intelligent Robots and Systems, pp. 468–473 (2000)
Giachetti, A., Campani, M., Torre, V.: The use of optical flow for road navigation. IEEE Transactions on Robotics and Automation 14(1), 34–48 (1998)
Barron, J., Fleet, D., Beauchemin, S.: Performance of optical flow techniques. International Journal of Computer Vision 12(1), 43–77 (1994)
Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: IJCAI. Proc. of the 7th Int. Joint Conf. on Artificial Intelligence, pp. 674–679 (1981)
Nagle, M.G., Srinivasan, M.V., Wilson, D.L.: Image interpolation technique for measurement of egomotion in 6 degrees of freedom. Journal of the Optical Society of America A: Optics, Image Science, and Vision 14(12), 3233–3241 (1997)
Newman, P., Ho, K.: Slam- loop closing with visually salient features. In: IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 635–642. IEEE Computer Society Press, Los Alamitos (2005)
de la Hamette, P., Tröster, G.: Architecture and applications of the fingermouse: a smart stereo camera for wearable computing HCI. Personal and Ubiquitous Computing (online first) (2007)
Campbell, J., Sukthankar, R., Nourbakhsh, I.: Techniques for evaluating optical flow for visual odometry in extreme terrain. In: Proc. of Intelligent Robots and Systems (IROS), pp. 3704–3711 (2004)
Srinivasan, M.V.: An image-interpolation technique for the computation of optic flow and egomotion. Biological Cybernetics 71(5), 401–415 (1994)
Liu, S.C.: A neuromorphic avlsi model of global motion processing in the fly. IEEE Trans. on Circuits and Systems 47(12), 1458–1467 (2000)
Stocker, A., Douglas, R.: Analog integrated 2D optical flow sensor with programmable pixels. In: Int. Symposium on Circuits and Systems ISCAS, pp. 121–138 (2004)
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Roggen, D., Jenny, R., de la Hamette, P., Tröster, G. (2007). Mapping by Seeing – Wearable Vision-Based Dead-Reckoning, and Closing the Loop. In: Kortuem, G., Finney, J., Lea, R., Sundramoorthy, V. (eds) Smart Sensing and Context. EuroSSC 2007. Lecture Notes in Computer Science, vol 4793. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75696-5_2
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DOI: https://doi.org/10.1007/978-3-540-75696-5_2
Publisher Name: Springer, Berlin, Heidelberg
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