[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

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90 Z. Kuś and A. Nawrat [3] Irani, M., Peleg, S.: Improving resolution by image registration. CVGIP: Graph. Modelsand Image Process. 53, 231–239 (1991) [4] Chesnaud, C., Refegier, P., Boulet, V.: Statistical region snake-based segmentation adapted to different physical noise models. IEEE Trans. Patt. Anal. Mach. Intell. 21, 1145–1157 (1999) [5] Gordon, N., Ristic, B., Arulampalam, S.: Beyond the Kalman Filter: Particle Filters for Tracking Applications. Artech House, Boston (2004) [6] Sharp, C., Shakernia, O., Sastry, S.: A Vision System for Landing an Unmanned Aerial Vehicle. In: Proceedings of the 2001 IEEE International Conference on Robotics and Automation, vol. 2, pp. 1720–1727. IEEE, Los Alamitos (2001) [7] Casbeer, D., Li, S., Beard, R., Mehra, R., McLain, T.: Forest Fire Monitoring With Multiple Small UAVs, Porland, OR (April 2005) [8] Kuś, Z., Fraś, S.: Helicopter control algorithms from the set orientation to the set geographical location. In: Nawrat, A., Simek, K., Świerniak, A. (eds.) Advanced Technologies for Intelligent Systems of National Border Security. SCI, vol. 440, pp. 3–14. Springer, Heidelberg (2013) [9] Nawrat, A.: Modelowanie i sterowanie bezzałogowych obiektów latających. Wydawnictwo Politechniki Slaskiej, Gliwice (2009) [10] Valavanis, K.P. (ed.): Advances In Unmanned Aerial Vehicles. Springer (2007) [11] Castillo, P., Lozano, R., Dzul, A.E.: Modelling and Control of Mini-Flying Machines. Springer (2005) [12] Padfield, G.D.: Helicopter Flight Dynamics. Backwell Science Ltd. (1996) [13] Manerowski, J.: Identyfikacja modeli dynamiki ruchu sterowanych obiektów lataja˛cych, WN ASKON, Warszawa (1999) [14] Kearney, J.K., Thompson, W.B.: Optical flow estimation: An error analysis of gradient-based methods with local optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence 9, 229–243 (1987) [15] Anandan, P.: A computational framework and an algorithm for the measurement of visual motion. International Journal of Computer Vision 2, 283–310 (1989) [16] Barman, H., Haglund, L., Knutsson, H., Granlund, G.: Estimation of velocity, acceleration, and disparity in time sequences. In: Proc. IEEE Workshop on Visual Motion, Princeton, NJ, pp. 44–51 (1991) [17] Bascle, B., Bouthemy, E., Deriche, N., Meyer, E.: Tracking complex primitives in an image sequence. In: Proc. 12th International Conference on Pattern Recognition, Jerusalem, pp. 426–431 (1994) [18] Butt, E.J., Yen, C., Xu, X.: Local correlation measures for motion analysis: A comparativestudy. In: Pattern Recognition and Image Processing Conference, Las Vegas, pp. 269–274 (1982) [19] Butt, E.J., Bergen, J.R., Hingorani, R., Kolczynski, R., Lee, W.A., Leung, A., Lubin, J., Shvayster, H.: Object tracking with a moving camera. In: Proc. IEEE Workshop on Visual Motion, Irving, pp. 2–12 (1989) [20] Buxton, B.E., Buxton, H.: Computation of optical flow from the motion of edges features in image sequences. Image and Vision Computing 2(2), 59–75 (1984) [21] Campani, M., Verri, A.: Computing optical flow from an overconstrained system oflinear algebraic equations. In: Proc. 3rd International Conference on Computer Vision, Osaka, pp. 22–26 (1990) [22] Campani, M., Verri, A.: Motion analysis from firstorder properties of optical flow. CVGIP: Image Understanding 56(1), 90–107 (1992) [23] Carlsson, S.: Information in the geometric structure of retinal flow field. In: Proc. 2nd International Conference on Computer Vision, pp. 629–633 (1988) [24] Gessing, R.: Control Fundamentals. Silesian University of Technology, Gliwice (2004)
Object Tracking in a Picture during Rapid Camera Movements 91 [25] Babiarz, A., Jaskot, K., Koralewicz, P.: The control system for autonomous mobile platform. In: Nawrat, A., Simek, K., Świerniak, A. (eds.) Advanced Technologies for Intelligent Systems. SCI, vol. 440, pp. 15–28. Springer, Heidelberg (2013) [26] Babiarz, A., Jaskot, K.: The concept of collision-free path planning of UAV objects. In: Nawrat, A., Simek, K., Świerniak, A. (eds.) Advanced Technologies for Intelligent Systems. SCI, vol. 440, pp. 81–94. Springer, Heidelberg (2013) [27] Jaskot, K., Babiarz, A.: The inertial measurement unit for detection of position. Przegląd Elektrotechniczny 86, 323–333 (2010) [28] Kostrzewa, D., Josiński, H.: Verification of the search space exploration strategy based on the solutions of the join ordering problem. In: Czachórski, T., Kozielski, S., Stańczyk, U. (eds.) Man-Machine Interactions 2. AISC, vol. 103, pp. 447–455. Springer, Heidelberg (2011) [29] Demski, P., Mikulski, M., Koteras, R.: Characterization of Hokuyo UTM-30LX laser range finder for an autonomous mobile robot. In: Nawrat, A., Simek, K., Świerniak, A. (eds.) Advanced Technologies for Intelligent Systems. SCI, vol. 440, pp. 143–153. Springer, Heidelberg (2013) [30] Skorkowski, A., Topor-Kaminski, T.: Analysis of EGNOS-augmented receiver positioning accuracy. Acta Physica Polonica A 122(5), 821–824 (2012) [31] Daniec, K., Jedrasiak, K., Koteras, R., Nawrat, A.: Embedded micro inertial navigation system. Applied Mechanics and Materials 249-250, 1234–1246 (2013) [32] Iwaneczko, P., Jędrasiak, K., Daniec, K., Nawrat, A.: A prototype of unmanned aerial vehicle for image acquisition. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2012. LNCS, vol. 7594, pp. 87–94. Springer, Heidelberg (2012) [33] Jędrasiak, K., Nawrat, A., Wydmańska, K.: SETh-link the distributed management system for unmanned mobile vehicles. In: Nawrat, A., Simek, K., Świerniak, A. (eds.) Advanced Technologies for Intelligent Systems. SCI, vol. 440, pp. 247–256. Springer, Heidelberg (2013)
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Studies in Computational Intelligen
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Aleksander Nawrat · Zygmunt Kuś E
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“In God We Trust, All others we o
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VIII Preface valuable information i
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Contents Part I: Design of Object D
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Contents XIII Technology Developmen
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XVI List of Contributors Adam Czorn
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XVIII List of Contributors Henryk M
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XX List of Contributors Józef Wron
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2 Design of Object Detection, Recog
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4 A. Babiarz et al. 1 Introduction
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6 A. Babiarz et al. The description
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8 A. Babiarz et al. a) b) Fig. 5. T
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10 A. Babiarz et al. o o o “micvo
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12 A. Babiarz et al. a) b) Fig. 7.
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14 A. Babiarz et al. • The camera
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16 A. Babiarz et al. the camera ser
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18 A. Babiarz et al. a) b) Fig. 11.
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20 A. Babiarz et al. patrol point i
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Recognition and Location of Objects
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Vision System for Group of Mobile R
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A Distributed Control Group of Mobi
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178 D. Bereska et al. The aim of th
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184 D. Bereska et al. 4.1 Mechanica
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186 D. Bereska et al. 4.1.3 Open-Lo
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188 D. Bereska et al. Fig. 16. Comp
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Probabilistic Approach to Planning
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206 Practical Applications of Class
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208 M. Mellado and K. Skrzypczyk an
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210 M. Mellado and K. Skrzypczyk a
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Prototyping the Autonomous Flight A
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Feature Extraction and HMM-Based Cl
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248 K. Daniec et al. In this articl
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250 K. Daniec et al. Fig. 2. Applic
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252 K. Daniec et al. by the ability
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254 K. Daniec et al. The idea of us
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280 A. Nawrat et al. • 1-phase el
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284 A. Nawrat et al. Table 1. Compa
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286 A. Nawrat et al. P3 P3 P3 71101
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288 A. Nawrat et al. S, VA 4,510 4,
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Technology Development of Military
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344 Conclusions Control algorithms
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[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

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