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(More customer reviews)This book presents two approaches for camera calibration. The first approach explains the photogrammetric principles of camera calibration. The second one explains the computer vision point of view. Photogrammetry by its very nature aims at rigorous modeling from images. Therefore, the physical and the geometric aspects of camera calibration are treated in great depth. In addition, the random component associated with the observed information is treated in a correct statistical sense. The collinearity model is central to most of the photogrammetric calibration algorithms. On the other hand, computer vision algorithms, in general, mainly concentrate on producing quick and fast algorithms to comply with the nature of their applications. Linear models are the driving force behind most of these algorithms. There is a great synergy between the two approaches if it exploited with a deep understanding. Well-known researchers in photogrammetry and computer vision author this book. I recommend this book.
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This book brings together concepts and approaches from the fields of photogrammetry and computer vision. In particular, it examines techniques relating to quantitative image analysis, such as orientation, camera modelling, system calibration, self-calibration and error handling. The chapters have been contributed by experts in the relevant fields, and there are examples from automated inspection systems and other real-world cases. The book provides study material for students, researchers, developers and practitioners.
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