Abstract
In this paper, we propose a data index structure which is constructed by a small autonomous mobile robot so that it manages millions of subimages it takes during a navigation of dozens of minutes. The subimages are managed according to a similarity measure between a pair of subimages, which is based on a method for quantizing HSV colors. The data index structure has been inspired by the CF tree of BIRCH, which is an early work in data squashing, though care and inventions were necessary as the bins of HSV colors are highly correlated. We also propose an application for peculiar subimage detection by the robot, which exploits the data index structures for the current image and another one for all images in its navigation. Experiments conducted in a private office of about 25m 2 proved the feasibility of the data index structure and the effectiveness of the peculiar subimage detection.
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Ando, S., Thanomphongphan, T., Hoshino, D., Seki, Y., Suzuki, E.: ACE: Anomaly Clustering Ensemble for Multi-perspective Anomaly Detection. In: Proc. SDM 2011, pp. 1–12 (2011)
DuMouchel, W., Volinsky, C., Johnson, T., Cortes, D.P.C.: Squashing Flat Files Flatter. In: Proc. KDD 1999, pp. 6–15 (1999)
Inatani, S., Suzuki, E.: Data Squashing for Speeding Up Boosting-Based Outlier Detection. In: Hacid, M.-S., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds.) ISMIS 2002. LNCS (LNAI), vol. 2366, pp. 601–611. Springer, Heidelberg (2002)
Kargupta, H., et al.: VEDAS: A Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring. In: Proc. SDM 2004, pp. 300–311 (2004)
Lei, Z., Fuzong, L., Bo, Z.: A CBIR Method Based on Color-spatial Feature. In: Proc. TENCON 1999, pp. 166–169 (1999)
Nakamoto, K., Yamada, Y., Suzuki, E.: Fast Clustering for Time-series Data with Average-time-sequence-vector Generation Based on Dynamic Time Warping. Trans. Japanese Soc. Artificial Intelligence 18(3), 144–152 (2002) (in Japanese)
Patist, J.P.: Fast Online Estimation of the Joint Probability Distribution. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 689–696. Springer, Heidelberg (2008)
Torralba, A., Fergus, R., Weiss, Y.: Small Codes and Large Image Databases for Recognition. In: Proc. CVPR 2008 (2008)
Urmson, C., et al.: Autonomous Driving in Urban Environments: Boss and the Urban Challenge. J. Field Robotics 25(8), 425–466 (2008)
Zhang, T., Ramakrishnan, R., Livny, M.: BIRCH: A New Data Clustering Algorithm and its Applications. Data Mining and Knowledge Discovery 1(2), 141–182 (1997)
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Suzuki, E., Matsumoto, E., Kouno, A. (2012). Data Squashing for HSV Subimages by an Autonomous Mobile Robot. In: Ganascia, JG., Lenca, P., Petit, JM. (eds) Discovery Science. DS 2012. Lecture Notes in Computer Science(), vol 7569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33492-4_10
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DOI: https://doi.org/10.1007/978-3-642-33492-4_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33491-7
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