By Shengyong Chen, Y. F. Li, Jianwei Zhang, Wanliang Wang
This specific booklet explores the $64000 concerns in learning for lively visible notion. The book’s 11 chapters draw on fresh vital paintings in robotic imaginative and prescient over ten years, rather within the use of latest thoughts. Implementation examples are supplied with theoretical tools for trying out in a true robotic procedure. With those optimum sensor making plans recommendations, this booklet will provide the robotic imaginative and prescient process the adaptability wanted in lots of functional functions.
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Additional info for Active Sensor Planning for Multiview Vision Tasks
About 20 years ago, Bajcsy discussed the important concept of active perception (Bajcsy 1988). Together with other researchers” initial contributions at that time, the new concept (compared with the Marr paradigm in 1982) on active perception, and consequently the sensor planning problem, was thus issued in vision research. The difference between the concepts of active perception and the Marr paradigm is that the former considers vision perception as the intentional action of the mind but the latter considers it as the procedural process of matter.
1995) proposed to set the viewpoint, look direction, and focal length of a camera. With a partially known environment, it dealt with two problems: how to determine the sensor”s pose (in the bootstrap phase) and how to determine the next-look direction (in the run phase). It took into account errors in the object position stored in the memory and errors due to image segmentation. Rosenfeld et al. (1988) discussed some techniques and relationship between object recognition and known or unknown viewpoints.
To date, there are more than two hundred research papers which mainly focus on sensor placement or viewpoint planning. At the early stage, these works were focused on sensor modeling, analysis of sensors” optical and geometrical parameters, and sensor placement constraints. From 1990 to 1995, most of these research works were CAD model-based and usually for applications in computer inspection or recognition. The generate-and-test method and the synthesis method are major contributions at that stage.