000			04229nam a2200421 i 4500
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007			cr nn 008mamaa
008			220601s2006 sz | o |||| 0|eng d
020			_a9783031022418
024	7		_a10.1007/978-3-031-02241-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aT385 _b2006 EB
100	1		_aZhang, Cha _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686427
245	1	0	_aLight Field Sampling _cby Cha Zhang, Tsuhan Chen
250			_a1st edition 2006
264		1	_aCham _bSpringer International Publishing _c2006
300			_a1 recurso en línea (XCVIII, 6 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Image Video and Multimedia Processing _x1559-8144
505	0		_aThe Light Field -- Light Field Spectral Analysis -- Light Field Uniform Sampling -- The Freeform Sampling Framework -- Light Field Active Sampling -- The Self-Reconfigurable Camera Array -- Conclusions and Future Work.
520			_aLight field is one of the most representative image-based rendering techniques that generate novel virtual views from images instead of 3D models. The light field capture and rendering process can be considered as a procedure of sampling the light rays in the space and interpolating those in novel views. As a result, light field can be studied as a high-dimensional signal sampling problem, which has attracted a lot of research interest and become a convergence point between computer graphics and signal processing, and even computer vision. This lecture focuses on answering two questions regarding light field sampling, namely how many images are needed for a light field, and if such number is limited, where we should capture them. The book can be divided into three parts. First, we give a complete analysis on uniform sampling of IBR data. By introducing the surface plenoptic function, we are able to analyze the Fourier spectrum of non-Lambertian and occluded scenes. Given the spectrum, we also apply the generalized sampling theorem on the IBR data, which results in better rendering quality than rectangular sampling for complex scenes. Such uniform sampling analysis provides general guidelines on how the images in IBR should be taken. For instance, it shows that non-Lambertian and occluded scenes often require a higher sampling rate. Next, we describe a very general sampling framework named freeform sampling. Freeform sampling handles three kinds of problems: sample reduction, minimum sampling rate to meet an error requirement, and minimization of reconstruction error given a fixed number of samples. When the to-be-reconstructed function values are unknown, freeform sampling becomes active sampling. Algorithms of active sampling are developed for light field and show better results than the traditional uniform sampling approach. Third, we present a self-reconfigurable camera array that we developed, which features a very efficient algorithm for real-time rendering and the ability of automatically reconfiguring the cameras to improve the rendering quality. Both are based on active sampling. Our camera array is able to render dynamic scenes interactively at high quality. To the best of our knowledge, it is the first camera array that can reconfigure the camera positions automatically.
988			_aSynthesis Collection of Technology_2006
650		7	_2embne _9143900 _aDiseño asistido por ordenador
650		7	_2embne _9141143 _aGráficos de ordenador
700	1		_aChen, Tsuhan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686428 _d1965-
776	0	8	_iPrinted edition: _z9783031011139
776	0	8	_iPrinted edition: _z9783031033698
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02241-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_dz _eb _zSI _b02/2023