000 03708nam a22004935i 4500
001 978-1-4471-4216-4
003 DE-He213
005 20140220083237.0
007 cr nn 008mamaa
008 120710s2012 xxk| s |||| 0|eng d
020 _a9781447142164
_9978-1-4471-4216-4
024 7 _a10.1007/978-1-4471-4216-4
_2doi
050 4 _aTA1637-1638
050 4 _aTA1637-1638
072 7 _aUYT
_2bicssc
072 7 _aUYQV
_2bicssc
072 7 _aCOM012000
_2bisacsh
072 7 _aCOM016000
_2bisacsh
082 0 4 _a006.6
_223
082 0 4 _a006.37
_223
100 1 _aMartínez-Martín, Ester.
_eauthor.
245 1 0 _aRobust Motion Detection in Real-Life Scenarios
_h[electronic resource] /
_cby Ester Martínez-Martín, Ángel P. del Pobil.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2012.
300 _aXII, 108 p. 70 illus., 61 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5768
505 0 _aIntroduction -- Motion Detection in Static Backgrounds -- Motion Detection in General Backgrounds -- Applications -- Computer Vision Terms.
520 _aOur knowledge of the surrounding world is obtained by our senses, of which vision is the most important for the information it can provide. In artificial systems, the field of Computer Vision aims to identify physical objects and scenes from captured images, to make useful decisions. This involves the processing and analysis of images, video data, and multi-dimensional data like medical scans. In this context, motion provides a stimulus for detecting objects in movement within the observed scene. Moreover, motion allows other characteristics to be obtained, such as object shape, speed or trajectory, which are meaningful for detection and recognition. However, the motion observable in a visual input can be due to different factors: movement of the imaged objects, movement of the observer, motion of the light sources, or a combination of these. This work focuses on motion detection from images captured by perspective and fisheye still cameras, proposing a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images is studied, allowing a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement against a dynamic background. This permits the development of a surveillance mechanism that removes the constraint of observing a scene free of foreground elements to obtain a reliable background model, since this situation cannot be guaranteed when operating in an unknown environment. Other problems are also addressed for the successful handling of changes in illumination, the distinction between foreground and background elements, and non-uniform vacillating backgrounds.
650 0 _aComputer science.
650 0 _aComputer vision.
650 1 4 _aComputer Science.
650 2 4 _aImage Processing and Computer Vision.
700 1 _aPobil, Ángel P. del.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781447142157
830 0 _aSpringerBriefs in Computer Science,
_x2191-5768
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-4216-4
912 _aZDB-2-SCS
999 _c100777
_d100777