000 03709nam a22005175i 4500
001 978-3-031-01813-8
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008 220601s2015 sz | s |||| 0|eng d
020 _a9783031018138
_9978-3-031-01813-8
024 7 _a10.1007/978-3-031-01813-8
_2doi
050 4 _aTA1501-1820
050 4 _aTA1634
072 7 _aUYT
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYT
_2thema
082 0 4 _a006
_223
100 1 _aElgammal, Ahmed.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980169
245 1 0 _aBackground Subtraction
_h[electronic resource] :
_bTheory and Practice /
_cby Ahmed Elgammal.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXVI, 67 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Computer Vision,
_x2153-1064
505 0 _aPreface -- Acknowledgments -- Figure Credits -- Object Detection and Segmentation in Videos -- Background Subtraction from a Stationary Camera -- Background Subtraction from a Moving Camera -- Bibliography -- Author's Biography .
520 _aBackground subtraction is a widely used concept for detection of moving objects in videos. In the last two decades there has been a lot of development in designing algorithms for background subtraction, as well as wide use of these algorithms in various important applications, such as visual surveillance, sports video analysis, motion capture, etc. Various statistical approaches have been proposed to model scene backgrounds. The concept of background subtraction also has been extended to detect objects from videos captured from moving cameras. This book reviews the concept and practice of background subtraction. We discuss several traditional statistical background subtraction models, including the widely used parametric Gaussian mixture models and non-parametric models. We also discuss the issue of shadow suppression, which is essential for human motion analysis applications. This book discusses approaches and tradeoffs for background maintenance. This book also reviews many of the recent developments in background subtraction paradigm. Recent advances in developing algorithms for background subtraction from moving cameras are described, including motion-compensation-based approaches and motion-segmentation-based approaches. For links to the videos to accompany this book, please see sites.google.com/a/morganclaypool.com/backgroundsubtraction/ Table of Contents: Preface / Acknowledgments / Figure Credits / Object Detection and Segmentation in Videos / Background Subtraction from a Stationary Camera / Background Subtraction from a Moving Camera / Bibliography / Author's Biography.
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_980170
650 0 _aPattern recognition systems.
_93953
650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aComputer Vision.
_980171
650 2 4 _aAutomated Pattern Recognition.
_931568
710 2 _aSpringerLink (Online service)
_980172
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031006852
776 0 8 _iPrinted edition:
_z9783031029417
830 0 _aSynthesis Lectures on Computer Vision,
_x2153-1064
_980173
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01813-8
912 _aZDB-2-SXSC
942 _cEBK
999 _c84911
_d84911