[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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60 Z. Kuś and A. Nawrat Fig. 2. Camera rotation angles as projection on a (x,y) plane Fig. 3. Camera rotation angles on a projection vertical plane S The direction of an axis z is a reference direction for defining the camera rotation angle in a vertical plane (cf. fig. 3). It is assumed that the camera may rotate within the range of 0 to 90 degrees. It denotes that 0°, 90°. The range of the camera rotation in vertical plane, as shown in figure 3, is sufficient regarding the following assumption: the first step comprises of setting the camera in an (x, y) plane towards an object which guarantees that in the second step the camera is being set in a vertical plane towards the object. Figure 4 presents spatial distribution of the camera and object before and after distortion.
Object Tracking for Rapid Camera Movements in 3D Space 61 Fig. 4. Spatial distribution of the camera and object before and after distortion Fig. 5. Camera rotation angles and locations in a projection on an (x,y) plane before and after distortion According to figure 4 we assume the following terms: , , - the camera coordinates before distortion; , , - the camera coordinates after distortion; - the distance between the object and the camera measured before distortion;
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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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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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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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Selection of Individual Gait Featur
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274 A. Nawrat et al. alia weather c
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276 A. Nawrat et al. have an embedd
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278 A. Nawrat et al. particular cha
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280 A. Nawrat et al. • 1-phase el
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282 A. Nawrat et al. The phase cond
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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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290 A. Nawrat et al. Comparison dif
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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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