Optimization plays an invaluable role in the exciting and
rapidly developing field of computer vision, yet this importance is
often overlooked in the literature.
This practical and authoritative text/reference presents a broad
introduction to the optimization methods used specifically in
computer vision. In order to facilitate understanding, the
presentation of the methods is supplemented by simple flow charts,
followed by pseudocode implementations that reveal deeper insights
into their mode of operation. These discussions are further
supported by examples taken from important applications in computer
vision.
Topics and features: provides a comprehensive overview of
computer vision-related optimization; covers a range of techniques
from classical iterative multidimensional optimization to
cutting-edge topics of graph cuts and GPU-suited total
variation-based optimization; describes in detail the optimization
methods employed in computer vision applications; illuminates key
concepts with clearly written and step-by-step explanations;
presents detailed information on implementation, including
pseudocode for most methods.
This easy-to-follow and applications-focused book is an
essential resource for researchers and practitioners seeking
guidance on implementing specific methods in computer vision.
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