[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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62 Z. Kuś and A. Nawrat , , - the tracked object coordinates, assuming 0; - point on the (x, y) plane visible in the center of the camera picture after distortion. Furthermore, figure 4 indicates on the fact that distortion moved the camera towards the center of the coordinates system , and it additionally increased the camera level above the ground The camera rotation angles in planes (x, y) and S were changed as well. Figure 5 represents the changes of angles in a greater detail. Figure 5 depicts notations for camera locations and rotations in relation to the object. It is a projection on an (x, y) plane before and after distortion. According to figure 5 we assume the following terms: - the angle of a camera deviation in a projection on an (x, y) plane when the camera is directed towards the object (before distortion); - the angle of a camera deviation in a projection on an (x, y) plane when the camera is not directed towards the object (after distortion); - the angle of a camera rotation in a projection on an (x, y) plane which compensates distortion (the camera is directed towards the object); - the angle in a projection on an (x, y) plane which defines direction towards the object; - the distance between the object and the camera in a projection on an (x, y) plane measured before distortion; - the distance between the object and the camera in a projection on an (x, y) plane measured after distortion; Figure 6 depicts notations for camera locations and rotations in relation to the object. It is a projection on an plane before and after distortion. Fig. 6. Camera rotation angles and locations in a projection on a plane S before and after distortion
Object Tracking for Rapid Camera Movements in 3D Space 63 According to figure 6 we assume the following terms: - the angle of a camera deviation from the vertical direction when the camera is directed towards the object (before distortion) ; - the angle of a camera deviation from the vertical direction when the camera is not directed towards the object (after distortion); When the first step of control algorithm is performed and the camera is set in an (x, y) plane towards an object then it is possible to calculate a correction angle in an plane. The location of the camera and the object on an S plane after the correction on an (x, y) plane is presented in figure 7. According to figure 7 we assume the following terms: - the angle in a projection on the plane which defines direction towards the object; - the angle of a camera rotation in a projection on the plane which compensates distortion. The camera settings changes, which will occur after distortion, aim at turning the camera head in such a way which allows the object to appear in the camera field of view. Similarly, as it was presented in [25], we assume that when the object is in the center of the field of view then 0 otherwise 0. is a signal produced by the image processing system. Hence we assume that in the moment of object position computing ( 0) the object is directly in the axis of the camera. The first step of control algorithm comprises of computing of the object location before distortion. The position of the object , , is calculated on the basis of rangefinder data (distance d), GPS[30] and IMU , , , , : · sin 90° · cos 90° 0°, 180° (1.1) · sin 90° · cos 90° 0°, 180° (1.2) As was it mentioned above, it is assumed that during object position calculation the object is in the center of the field of view. The aforementioned calculations are processed during the helicopter flight when 0. The manifestation of distortion is the loss of the object in the picture and considerable changes of the object position or orientation. Then the helicopter control system turns the helicopter to a nearly horizontal position. Afterwards , , , , are measured. The goal of the control algorithm is to turn the camera towards the object. Required values of camera tilt angles and are calculated on the basis of the object and camera positions. These angles are calculated by the equations stated below:
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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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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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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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