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Underwater Computer Vision
Fouad Sabry
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Naturwissenschaften, Medizin, Informatik, Technik / Informatik, EDV
Beschreibung
What is Underwater Computer Vision
Underwater computer vision is a subfield of computer vision. In recent years, with the development of underwater vehicles, the need to be able to record and process huge amounts of information has become increasingly important. Applications range from inspection of underwater structures for the offshore industry to the identification and counting of fishes for biological research. However, no matter how big the impact of this technology can be to industry and research, it still is in a very early stage of development compared to traditional computer vision. One reason for this is that, the moment the camera goes into the water, a whole new set of challenges appear. On one hand, cameras have to be made waterproof, marine corrosion deteriorates materials quickly and access and modifications to experimental setups are costly, both in time and resources. On the other hand, the physical properties of the water make light behave differently, changing the appearance of a same object with variations of depth, organic material, currents, temperature etc.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Underwater computer vision
Chapter 2: Computer vision
Chapter 3: Hydrographic survey
Chapter 4: Autonomous underwater vehicle
Chapter 5: Monterey Bay Aquarium Research Institute
Chapter 6: Unmanned underwater vehicle
Chapter 7: Noise reduction
Chapter 8: Underwater vision
Chapter 9: Video post-processing
Chapter 10: Image quality
(II) Answering the public top questions about underwater computer vision.
(III) Real world examples for the usage of underwater computer vision in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Underwater Computer Vision.
Kundenbewertungen
Monterey Bay Aquarium Research Institute, Noise reduction, Underwater computer vision, Hydrographic survey, Autonomous underwater vehicle, Computer vision, Unmanned underwater vehicle