[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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240 H. Josiński et al. graphically for the clarity of figures. In the former case the experimental results were remarkably worse than for greater values of d. On the other hand, classification accuracy in the latter case was equal to 100 % without exception. Fig. 4. Dependency between CCR and number N of states for PCA Analogical results received in case of the LLE for k = 20, 40, 80, 160 are presented in Fig. 5, 6, 7, 8, respectively. Fig. 5. Dependency between CCR and number N of states for LLE using 20 neighbors
Feature Extraction and HMM-Based Classification of Gait Video Sequences 241 Fig. 6. Dependency between CCR and number N of states for LLE using 40 neighbors Fig. 7. Dependency between CCR and number N of states for LLE using 80 neighbors Fig. 8. Dependency between CCR and number N of states for LLE using 160 neighbors
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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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22 A. Babiarz et al. particular ang
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24 A. Babiarz et al. The sample cod
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Recognition and Location of Objects
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48 P. Demski et al. Fig. 1. Automat
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50 P. Demski et al. E-Grip firing m
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52 P. Demski et al. 4 Automatic Tar
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54 P. Demski et al. implementing su
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Object Tracking for Rapid Camera Mo
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Object Tracking in a Picture during
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94 Construction of Image Acquisitio
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96 G. Bieszczad et al. effectivenes
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98 G. Bieszczad et al. such a way t
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100 G. Bieszczad et al. Table 1. No
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102 G. Bieszczad et al. Fig. 7. Pri
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104 G. Bieszczad et al. Fig. 10. Re
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106 G. Bieszczad et al. Fig. 13. Ti
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108 G. Bieszczad et al. Fig. 16. Op
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110 G. Bieszczad et al. has to make
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112 G. Bieszczad et al. MTF functio
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114 G. Bieszczad et al. [11] Krupi
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116 D. Bereska et al. Presented in
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118 D. Bereska et al. Fig. 2. Image
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120 D. Bereska et al. Fig. 4. Ortho
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Omnidirectional Video Acquisition D
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Part III Design of Vision Based Con
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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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180 D. Bereska et al. 3 Control Alg
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182 D. Bereska et al. Fig. 5. Schem
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184 D. Bereska et al. 4.1 Mechanica
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Technology Development of Military
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312 A. Czornik, A. Nawrat, and M. N
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328 M. Koźlak, A. Kurzeja, and A.
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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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