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Borga, M., Knutsson, H.: Estimating multiple depths in semi-transparent stereo images. Proc. Scandinavian Conf. on Image Analysis Vol. I (1999) 127--133. Kangerlussuaq, Greenland. Published by the Pattern Recognition Society of Denmark, Lyngby, Denmark.

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Multi-valued Images and Their Separation - Schechner, Kiryati, Shamir   (Correct)

....is disturbed by the superposition of adjacent defocused slices. Our goal is to clear the the disturbing crosstalk of the superimposing contributions, and gain information on the scene structure. Previous treatment of this situation has been based mainly on motion [3,7,9, 13,23,26] and stereo [4,22]. Polarization cues have been used for such scenarios in Refs. 8,12] Thorough polarization analysis, that enabled the labeling of the layers was done in [17,18,19,21] This paper refers to these methods, and deals also with the use of depth of field (DOF) to analyze images. DOF has been utilized ....

Borga, M., Knutsson, H.: Estimating multiple depths in semi-transparent stereo images. Proc. Scandinavian Conf. on Image Analysis Vol. I (1999) 127--133. Kangerlussuaq, Greenland. Published by the Pattern Recognition Society of Denmark, Lyngby, Denmark.


Multi-valued Images and Their Separation - Schechner, Kiryati, Shamir (2001)   (Correct)

....is disturbed by the superposition of adjacent defocused slices. Our goal is to clear the the disturbing crosstalk of the superimposing contributions, and gain information on the scene structure. Previous treatment of this situation has been based mainly on motion [3, 7, 9, 13,23, 26] and stereo [4, 22]. Polarization cues have been used for such scenarios 1 c Xxxx IEEE, Kluwer Academic Publishers, and the Optical Society of America. Parts of this paper were reproduced, with permission, from the Proc. Int. Conf. on Computer Vision, Vol. II, p. 814 819 (Kerkyra, 20 Sep 1999) Proc. Conf. on ....

Borga, M., Knutsson, H.: Estimating multiple depths in semi-transparent stereo images. Proc. Scandinavian Conf. on Image Analysis Vol. I (1999) 127-133. Kangerlussuaq, Greenland. Published by the Pattern Recognition Society of Denmark, Lyngby, Denmark. 12


Separation of Transparent Layers using Focus - Schechner, Kiryati, Basri (2000)   (7 citations)  (Correct)

....motion [58] We adopt this terminology, but stress the fact that this work does not deal with imaging through an object with variable opacity. Approaches to recovering each of the layers by nulling the others relied mainly on triangulation methods like motion [6, 12, 13, 22, 36, 49] and stereo [7, 48]. Algorithms were developed to cope with multiple superimposed motion elds [6, 49] and ambiguities in the solutions were discovered [47, 60] Another approach to the problem has been based on polarization cues [18, 20, 35, 41, 42, 43, 45] However, that approach needs a polarizing lter to be ....

Borga, M. and Knutsson, H. 1999. Estimating multiple depths in semi-transparent stereo images. Proc. Scandinavian Conf. on Image Analysis, Vol. I, Kangerlussuaq, Greenland. pp. 127-133. Published by the Pattern Recognition Society of Denmark, Lyngby, Denmark.


Multi-valued Images and Their Separation - Schechner, Kiryati, Shamir (2001)   (Correct)

....is disturbed bythe superposition of adjacent defocused slices. Our goal is to clear the the disturbing crosstalk of the superimposing contributions, and gain information on the scene structure. Previous treatment of this situation has been based mainly on motion [3, 7, 9, 13,23, 26] and stereo [4, 22]. Polarization cues have been used for such scenarios # c # Xxxx IEEE, Kluwer Academic Publishers, and the Optical Society of America. Parts of this paper were reproduced, with permission, from the Proc. Int. Conf. on Computer Vision, Vol. II, p. 814 819 (Kerkyra, 20 Sep 1999) Proc. Conf. on ....

Borga, M., Knutsson, H.: Estimating multiple depths in semi-transparent stereo images. Proc. Scandinavian Conf. on Image Analysis Vol. I (1999) 127-133. Kangerlussuaq, Greenland. Published bythePattern Recognition Society of Denmark, Lyngby, Denmark. 12


Separation of Transparent Layers using Focus - Schechner, Kiryati, Basri (1998)   (7 citations)  (Correct)

....motion [58] We adopt this terminology, but stress the fact that this work does not deal with imaging through an object with variable opacity. Approaches to recovering each of the layers by nulling the others relied mainly on triangulation methods like motion [6, 12, 13, 22, 36, 49] and stereo [7, 48]. Algorithms were developed to cope with multiple superimposed motion fields [6, 49] and ambiguities in the solutions were discovered [47, 60] Another approach to the problem has been based on polarization cues [18, 20, 35, 41, 42, 43, 45] However, that approach needs a polarizing filter to be ....

Borga, M. and Knutsson, H. 1999. Estimating multiple depths in semi-transparent stereo images. Proc. Scandinavian Conf. on Image Analysis, Vol. I, Kangerlussuaq, Greenland. pp. 127-133. Published by the Pattern Recognition Society of Denmark, Lyngby, Denmark.


Blind Recovery of Transparent and Semireflected Scenes - Yoav Schechner Nahum (2000)   (1 citation)  (Correct)

.... looking through a window, the object behind the window (real object [10, 11] is disturbed by a semi reflection of another object (virtual object) This situation was described using the term transparent layers [2, 20] Treatment has been based mainly on motion [2, 5, 7, 11, 18, 19] and stereo [3, 18]. Monocular methods were based on polarization [6, 10, 15, 16, 17] or on focus [14] The focus cue is based on the limited depth of field of the imaging system, and is useful also for separating and recovering three dimensional volumetric specimens acquired by microscopy (as in [1, 8, 9, 12] or ....

M. Borga and H. Knutsson, "Estimating multiple depths in semi-transparent stereo images," Proc. SCIA, Vol. I, pp. 127133


Finding Efficient Nonlinear Visual Operators using Canonical.. - Borga, Knutsson (2000)   Self-citation (Borga Knutsson)   (Correct)

....as complex quadrature lter pairs. Top two from canonical correlation vector 1. Bottom two from canonical correlation vector 2. Local disparity An important problem in computer vision that is suitable to handle with CCA is stereo vision, since data in this case naturally appear in pairs. In [4, 5] a novel stereo vision algorithm that combines CCA and phase analysis is presented. It is demonstrated that the algorithm can handle traditionally dicult problems such as: 1. Producing multiple disparity estimates for semi transparent images, see gure 6, 2. Maintain accuracy at disparity edges, ....

M. Borga and H. Knutsson. Estimating Multiple Depths in Semi-transparent Stereo Images. In Proceedings of the Scandinavian Conference on Image analysis, Greenland, June 1999. SCIA. Also as Technical Report LiTH-ISY-R-2248.

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