Abstract
This paper considers the problem of planning sensor observations for a network of overhead sensors which will resolve ambiguities in the output of a horizontal sensor network. Specifically, we address the problem of counting the number of objects detected by the horizontal sensor network, using the overhead network to aim at specific areas to improve the count. The main theme of our results is that, even though observation planning is intractable for such a network, a simple, greedy algorithm for controlling the overhead sensors guarantees performance with bounded and reasonable suboptimality. Our results are general and make few assumptions about the specific sensors used. The techniques described in this paper can be used to plan sensor aims for a wide variety of sensor types and counting problems.
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References
Chrobak, M., Payne, T.: A linear-time algorithm for drawing a planar graph on a grid. Information Processing Letters 54(4) (1989)
Fowler, R.J., Paterson, M.S., Tanimoto, S.L.: Optimal packing and covering in the plane are NP-Complete. Information Processing Letters 12, 133–137 (1981)
Guestrin, C., Krause, A., Singh, A.: Near-optimal sensor placements in gaussian processes. In: ICML (2005)
He, Y., Chong, E.: Sensor scheduling for target tracking: A Monte Carlo sampling approach. Digital Signal Processing 16, 533–545 (2006)
Laurentini, A.: The visual hull concept for silhouette-based image understanding. IEEE PAMI 16, 150–162 (1994)
Liu, X., Tu, P., Rittscher, J., Perera, A., Krahnstoever, N.: Detecting and counting people in surveillance applications. In: Advanced Video and Signal Based Surveillance (2005)
Masoud, O., Papanikolopoulos, N.: A novel method for tracking and counting pedestrians in real-time using a single camera. IEEE Transactions on Vehicular Technology 50(5), 1267–1278 (2001)
Nemhauser, G.L., Wolsey, L.A., Fisher, M.L.: An analysis of approximations for maximizing submodular set functions. Mathematical Programming 14, 265–294 (1978)
Särkkä, S., Vehtari, A., Lampinen, J.: Rao-blackwellized particle filter for multiple target tracking. Information Fusion Journal 8, 2–15 (2007)
Yang, D., Gonzalez-Banos, H., Guibas, L.: Counting people in crowds with a real-time network of simple image sensors. In: IEEE ICCV (2003)
Zhao, T., Nevatia, R.: Tracking multiple humans in crowded environment. In: IEEE CVPR, vol. 2, pp. 406–413 (2004)
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© 2009 Springer-Verlag Berlin Heidelberg
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Halvorson, E., Parr, R. (2009). Planning Aims for a Network of Horizontal and Overhead Sensors. In: Chirikjian, G.S., Choset, H., Morales, M., Murphey, T. (eds) Algorithmic Foundation of Robotics VIII. Springer Tracts in Advanced Robotics, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00312-7_2
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DOI: https://doi.org/10.1007/978-3-642-00312-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00311-0
Online ISBN: 978-3-642-00312-7
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