By Shengyong Chen, Y. F. Li, Jianwei Zhang, Wanliang Wang
This exact booklet explores the real matters in learning for energetic visible conception. The book’s 11 chapters draw on fresh very important paintings in robotic imaginative and prescient over ten years, relatively within the use of latest strategies. Implementation examples are supplied with theoretical equipment for checking out in a true robotic method. With those optimum sensor making plans ideas, this e-book will supply the robotic imaginative and prescient procedure the adaptability wanted in lots of functional purposes.
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Additional info for Active Sensor Planning for Multiview Vision Tasks
The lines are numbered from left to right. They are called Gray-Code, although they are in binary patterns. Using a controllable projector with 2n switchable lines, all lines may be encoded with n+1 bits, and projected with n+1 images. 3 Measurement Principle Projector Fw Lk , j C camera 3k 3 3j lj lk Fig. 16. The measurement principle 26 Chapter 2 Active Vision Sensors object [Xc Yc Zc], [Xp Yp Zp] light projection Zc [xp yp] Zp [xc yc] Xp projector Yc camera X Yp c Fig. 17. 17 illustrates the measurement principle in the stripe light system and Fig.
Tarabanis et al. (1995) presented an intensive survey on sensing strategies developed in the early stage, concentrated upon the period between 1987 and 1991. Among them, Cowan (1988) gave detailed descriptions on computing the acceptable viewpoints for satisfying many requirements (sensor placement constraints). In Cowan (1988), lens aperture setting was also considered by computing the diffraction limit. e. surface absorption, diffused reflectance, specular reflectance, and image irradiance. Abrams et al.
They combined the object recognition algorithm and the target distribution probability for the vision task. Ikeuchi et al. (1991) developed a sensor modeler, called VANTAGE, to place the light sources and cameras for object recognition. It mostly solves the detectability (visibility) of both light sources and cameras. Borotschnig et al. (2000) also presented an active vision system for recognizing objects which are ambiguous from certain viewpoints. The system repositions the camera to capture additional views and uses probabilistic object classifications to perform view planning.