Academic literature on the topic 'Shape-from-shadows'
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Journal articles on the topic "Shape-from-shadows"
Cavanagh, Patrick, and Yvan G. Leclerc. "Shape from shadows." Journal of Experimental Psychology: Human Perception and Performance 15, no. 1 (1989): 3–27. http://dx.doi.org/10.1037/0096-1523.15.1.3.
Full textHatzitheodorou, Michael. "Shape from Shadows." Journal of Complexity 14, no. 1 (March 1998): 63–84. http://dx.doi.org/10.1006/jcom.1997.0448.
Full textChappelow, J. E. "Simple impact crater shape determination from shadows." Meteoritics & Planetary Science 48, no. 10 (September 24, 2013): 1863–72. http://dx.doi.org/10.1111/maps.12201.
Full textCavanagh, Patrick, and Yvan G. Leclerc. ""Shape from shadows": Correction to Cavanagh and Leclerc (1989)." Journal of Experimental Psychology: Human Perception and Performance 16, no. 4 (1990): 910. http://dx.doi.org/10.1037/0096-1523.16.4.910.
Full textYamashita, Yukihiro, Fumihiko Sakaue, and Jun Sato. "Fast 3D Shape Recovery from Shadows Projected on Arbitrary Curved Surfaces." International Journal of Virtual Reality 9, no. 1 (January 1, 2010): 1–6. http://dx.doi.org/10.20870/ijvr.2010.9.1.2754.
Full textNorman, J. Farley, Thomas E. Dawson, and Shane R. Raines. "The Perception and Recognition of Natural Object Shape from Deforming and Static Shadows." Perception 29, no. 2 (February 2000): 135–48. http://dx.doi.org/10.1068/p2994.
Full textCastiello, Umberto, Dean Lusher, Carol Burton, and Peter Disler. "Shadows in the Brain." Journal of Cognitive Neuroscience 15, no. 6 (August 1, 2003): 862–72. http://dx.doi.org/10.1162/089892903322370780.
Full textNorman, J. F., Y. l. Lee, F. Phillips, H. F. Norman, L. R. Jennings, and T. R. McBride. "The perception of 3-D shape from shadows cast onto curved surfaces." Journal of Vision 9, no. 8 (March 24, 2010): 60. http://dx.doi.org/10.1167/9.8.60.
Full textNorman, J. Farley, Young-lim Lee, Flip Phillips, Hideko F. Norman, L. RaShae Jennings, and T. Ryan McBride. "The perception of 3-D shape from shadows cast onto curved surfaces." Acta Psychologica 131, no. 1 (May 2009): 1–11. http://dx.doi.org/10.1016/j.actpsy.2009.01.007.
Full textKoizumi, Tomomi, Hiroyuki Ito, Shoji Sunaga, and Masaki Ogawa. "Directional Bias in the Perception of Cast Shadows." i-Perception 8, no. 1 (January 2017): 204166951668226. http://dx.doi.org/10.1177/2041669516682267.
Full textDissertations / Theses on the topic "Shape-from-shadows"
Savarese, Silvio Perona Pietro. "Shape reconstruction from shadows and reflections /." Diss., Pasadena, Calif. : California Institute of Technology, 2005. http://resolver.caltech.edu/CaltechETD:etd-05242005-162056.
Full textJakobsson, Torbjörn. "Shape from shading, colour constancy, and deutan colour vision deficiencies." Doctoral thesis, Umeå universitet, Institutionen för psykologi, 1996. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-111106.
Full textDiss. (sammanfattning) Umeå : Umeå university, 1996, härtill 4 uppsatser
digitalisering@umu
Lee, Young-Lim. "The Perception and Recognition of 3-D Shape from Shadows Cast onto Curved Surfaces." TopSCHOLAR®, 2003. http://digitalcommons.wku.edu/theses/609.
Full textDraréni, Jamil. "Exploitation de contraintes photométriques et géométriques en vision : application au suivi, au calibrage et à la reconstruction." Grenoble, 2010. http://www.theses.fr/2010GRENM061.
Full textThe topic of this thesis revolves around three fundamental problems in computer vision; namely, video tracking, camera calibration and shape recovery. The proposed methods are solely based on photometric and geometric constraints found in the images. Video tracking, usually performed on a video sequence, consists in tracking a region of interest, selected manually by an operator. We extend a successful tracking method by adding the ability to estimate the orientation of the tracked object. Furthermore, we consider another fundamental problem in computer vision: calibration. Here we tackle the problem of calibrating linear cameras (a. K. A: pushbroom)and video projectors. For the former one we propose a convenient plane-based calibration algorithm and for the latter, a calibration algorithm that does not require aphysical grid and a planar auto-calibration algorithm. Finally, we pointed our third research direction toward shape reconstruction using coplanar shadows. This technique is known to suffer from a bas-relief ambiguity if no extra information on the scene or light source is provided. We propose a simple method to reduce this ambiguity from four to a single parameter. We achieve this by taking into account the visibility of the light spots in the camera
Savarese, Silvio. "Shape Reconstruction from Shadows and Reflections." Thesis, 2005. https://thesis.library.caltech.edu/2002/1/savarese_thesis.pdf.
Full textMeasuring automatically the shape of physical objects in order to obtain corresponding digital models has become a useful, often indispensable, tool in design, engineering, art conservation, computer graphics, medicine and science. Machine vision has proven to be more appealing than competing technologies. Ideally, we would like to be able to acquire digital models of generic objects by simply walking around the scene, while filming with a handheld camcorder. Thus, one of the main challenges in modern machine vision is to develop algorithms that: i) are inexpensive, fast and accurate; ii) can handle objects with arbitrary appearance properties and shape; and iii) need little or no user intervention.
In this thesis, we address both issues. In the first part, we present a novel 3D reconstruction technique which makes use of minimal and inexpensive equipment. We call this technique "shadow carving". We explore the information contained in the shadows that an object casts upon itself. An algorithm is provided that makes use of this information. The algorithm iteratively recovers an estimate of the object which i) approximates the object’s shape more and more closely; and ii) is provably an upper bound to the object's shape. Shadow carving is the first technique to incorporate "shadow" information in a multi-view shape recovery framework. We have implemented our approach in a simple table-top system and validated our algorithm by recovering the shape of real objects.
It is well known that vision-based 3D scanning systems handle specular or highly reflective surfaces only poorly. The cause of this deficiency is most likely not intrinsic, but rather due to our lack of understanding of the relevant cues. In the second part of this thesis, we focus on how to promote mirror reflections from "noise" to "signal". We first present a geometrical and algebraic characterization of how a patch of the scene is mapped into an image by a mirror surface of given shape. We then develop solutions to the inverse problem of deriving surface shape from mirror reflections in a single image. We validate our theoretical results with both numerical simulations and experiments with real surfaces.
A third goal of this thesis is advancing our understanding of human perception of shape from reflections. Although the idea of perception of shape from different visual cues (e.g., shading, texture, etc.) has been extensively discussed in the past, little is known to what extent highlights and specular reflections carry useful information for shape perception. We use psychophysics to study this capability. Our goal is to provide a benchmark, as well as inspire possible technical approaches, for our computational work. We find that surprisingly, humans are very poor at judging the shape of mirror surfaces when additional visual cues (i.e., contour, shading, stereo, texture) are not visible.
Books on the topic "Shape-from-shadows"
Ruxton, Graeme D., William L. Allen, Thomas N. Sherratt, and Michael P. Speed. Countershading. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199688678.003.0004.
Full textGarden, Alison. The Literary Afterlives of Roger Casement, 1899-2016. Liverpool University Press, 2020. http://dx.doi.org/10.3828/liverpool/9781789621815.001.0001.
Full textMatiazzi, Estevam. O Desvelar da Poesia. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-754-9.
Full textBook chapters on the topic "Shape-from-shadows"
Mamassian, Pascal. "Shape from Shadows." In Computer Vision, 724–25. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_260.
Full textMamassian, Pascal. "Shape from Shadows." In Computer Vision, 1148–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63416-2_260.
Full textFalcone, M., M. Sagona, and A. Seghini. "A scheme for the shape-from-shading model with “black shadows”." In Numerical Mathematics and Advanced Applications, 503–12. Milano: Springer Milan, 2003. http://dx.doi.org/10.1007/978-88-470-2089-4_47.
Full text"Shape Recovery from Shadows." In Physics-Based Vision: Principles and Practice, 363–404. A K Peters/CRC Press, 1993. http://dx.doi.org/10.1201/9781439865880-11.
Full textSorensen, Roy. "Parmenides." In Nothing, 77–89. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780199742837.003.0006.
Full textZallen, Jeremy. "Piney Lights." In American Lucifers, 57–93. University of North Carolina Press, 2019. http://dx.doi.org/10.5149/northcarolina/9781469653327.003.0003.
Full textConference papers on the topic "Shape-from-shadows"
Mecca, Roberto, Aaron Wetzler, Ron Kimmel, and Alfred Marcel Bruckstein. "Direct Shape Recovery from Photometric Stereo with Shadows." In 2013 International Conference on 3D Vision (3DV). IEEE, 2013. http://dx.doi.org/10.1109/3dv.2013.57.
Full textDickey, F. M., and A. W. Doerry. "Recovering shape from shadows in synthetic aperture radar imagery." In SPIE Defense and Security Symposium, edited by Kenneth I. Ranney and Armin W. Doerry. SPIE, 2008. http://dx.doi.org/10.1117/12.775610.
Full textPresles, B., J. Debayle, and J. C. Pinoli. "Shape recognition from shadows of 3-D convex geometrical objects." In 2012 19th IEEE International Conference on Image Processing (ICIP 2012). IEEE, 2012. http://dx.doi.org/10.1109/icip.2012.6466908.
Full textYamashita, Yukihiro, Fumihiko Sakaue, and Jun Sato. "Recovering 3D Shape and Light Source Positions from Non-planar Shadows." In 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.1153.
Full textTyler, Christopher W. "Diffuse illumination as a default assumption for shape-from-shading in the absence of shadows." In Electronic Imaging '97, edited by Bernice E. Rogowitz and Thrasyvoulos N. Pappas. SPIE, 1997. http://dx.doi.org/10.1117/12.274530.
Full textMatovic, J., A. Vujanic, and K. Reichenberger. "Variable Emissivity Surfaces for Micro and Nanosatellites." In CANEUS 2006: MNT for Aerospace Applications. ASMEDC, 2006. http://dx.doi.org/10.1115/caneus2006-11027.
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