[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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80 Z. Kuś and A. Nawrat According to figure 2 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, , - the tracked object coordinates, assuming $y_o=0$, - the angle of deviation of a camera from the vertical position when the camera is directed to the object (before distortion) , - the angle of deviation of a camera from the vertical position when the camera is not directed to the object (after distortion). The aim of the camera settings correction is to turn the head of the camera in a manner which allows the object to appear in the camera field of view. The figure 3 represents the object position in relation to the camera field of view. Furthermore, we assume that when the object is in the center of the field of view then 0. is a signal produced by the image processing system otherwise 0. Hence we assume that in the moment of object position computing ( 0) the object is directly in the axis of the camera. Fig. 3. The object position in the field of view of the camera The position of the object is calculated on the basis of rangefinder data (distance ), GPS [30] and IMU data , , : ·sin . (1) As was it mentioned above, it is assumed that the object is in the center of the field of view. The aforementioned calculations are processed during the helicopter
Object Tracking in a Picture during Rapid Camera Movements 81 flight. When there is distortion the object ceases to be visible in the picture. In the case of distortion it may be stated that there is no object in the picture and considerable changes of the object position or orientation appear. Then the helicopter control system turns the helicopter to a nearly horizontal position. Afterwards , , are measured. In the next step the correction angle is computed. The helicopter must be turned at this angle. As figure 4 presents the position and orientation of the camera are known. The position of the tracked object is known too. This position was calculated before distortion. The angle is calculated on the basis of camera and object positions. The angle is the angle of rotation which compensates distortion. Fig. 4. Terms of camera angles in relation to the tracked object Required value of camera tilt angle is calculated on the basis of the object and camera positions: (2) According to the terms in figure 4 it is obtained (3) It is necessary to account a sign of the angles. It depends on the object position in relation to the camera position.
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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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Omnidirectional Video Acquisition D
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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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212 M. Mellado and K. Skrzypczyk wh
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214 M. Mellado and K. Skrzypczyk Fi
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216 M. Mellado and K. Skrzypczyk 6
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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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