By Shengyong Chen, Y. F. Li, Jianwei Zhang, Wanliang Wang
This precise publication explores the real matters in learning for lively visible conception. The book’s 11 chapters draw on contemporary vital paintings in robotic imaginative and prescient over ten years, rather within the use of latest recommendations. Implementation examples are supplied with theoretical equipment for checking out in a true robotic procedure. With those optimum sensor making plans thoughts, this e-book will supply the robotic imaginative and prescient approach the adaptability wanted in lots of functional purposes.
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Extra resources for Active Sensor Planning for Multiview Vision Tasks
21) Since the system considered here has two DOFs, only two of the six parameters are variable while the other four are constants which can be known from the initial calibration. If the X-Z plane is not perpendicular to the plane of the projected laser sheet, its angle ) can also be identified at this stage. As the angle T0 =(90o –)) is small and the image can be rectified by rotating the corresponding angle accordingly during recalibration, it can be assumed that T0 = 0. The displacement in the y-direction between the camera center and the projector center, Y0, and the rotation angle E0 are also small in practice.
The device to calibrate the rotational center Surface reflection [Xc Yc Zc], [Xp Yp Zp] illumination optical axis Zc [xc yc vc] on projector Zp vc LCD b optical center Yc [xp yp vp] vp x (i on camera D Xc h D0 vp Xp optical center Yp Fig. 21. 3 Geometrical Constraint Assume a straight line in the scene which is expressed in the camera coordinate system and projected on the X-Z plane: Z c = C1 Xc + C2. 25): [b – hcot(Į)] (vc - C1 xc ) - C2 [vccot(Į) + xc] = 0. 26) If h = 0, the above can be simplified as b(vc - C1 xc ) - C2[vccot(Į0 + Įpi) + xc] =0.
Farag (2004) solves the planning problem for a mobile active system with a trinocular vision sensor (Fig. 3). An algorithm is proposed to combine a closed-form solution for the translation between the three cameras, the vergence angle of the cameras as well as zoom and focus setting with the results of the correspondences between the acquired images and a predefined target obtained using the Scale Invariant Feature Transform (SIFT) algorithm. There are two goals. The first is to detect the target objects in the navigation field.
Active Sensor Planning for Multiview Vision Tasks by Shengyong Chen, Y. F. Li, Jianwei Zhang, Wanliang Wang