Prof. Zygmunt Pizlo
Assistant Professor
SPIE Involvement:
Author | Instructor
Publications (26)

Proceedings Article | 6 September 2017 Paper
Eric Palmer, TaeKyu Kwon, Zygmunt Pizlo
Proceedings Volume 10410, 104101B (2017) https://doi.org/10.1117/12.2273061
KEYWORDS: Virtual reality, Visual system, 3D image reconstruction, Human vision and color perception, Computer simulations, Inverse problems, 3D image processing, 3D modeling, Machine vision, 3D vision

SPIE Journal Paper | 8 August 2016 Open Access
Aaron Michaux, Vijai Jayadevan, Edward Delp, Zygmunt Pizlo
JEI, Vol. 25, Issue 06, 061606, (August 2016) https://doi.org/10.1117/12.10.1117/1.JEI.25.6.061606
KEYWORDS: 3D image processing, Cameras, Mirrors, Stereoscopic cameras, Human vision and color perception, Visualization, Imaging systems, 3D modeling, Visual process modeling, Visual system

Proceedings Article | 3 February 2014 Paper
Proceedings Volume 9016, 90160E (2014) https://doi.org/10.1117/12.2048594
KEYWORDS: Visibility, Image compression, Image quality, Edge detection, Image processing, Optical filters, Molybdenum, Image filtering, Psychophysics, Tablets

Proceedings Article | 21 February 2012 Paper
Shao-Fu Xue, Qian Lin, Daniel Tretter, Seungyon Lee, Zygmunt Pizlo, Jan Allebach
Proceedings Volume 8302, 83020D (2012) https://doi.org/10.1117/12.914686
KEYWORDS: Photography, Machine vision, Computer vision technology, Image classification, Image quality, Digital photography, Image processing, Visualization, Image filtering, Multimedia

Proceedings Article | 21 February 2012 Paper
Aziza Satkhozhina, Ildus Ahmadullin, Seungyon Lee, Zygmunt Pizlo, Jan Allebach
Proceedings Volume 8302, 83020L (2012) https://doi.org/10.1117/12.910860
KEYWORDS: Visualization, Matrices, Human subjects, Databases, Expectation maximization algorithms, Algorithm development, MATLAB, Classification systems, Image classification, Image compression

Showing 5 of 26 publications
Conference Committee Involvement (10)
Computational Imaging XI
5 February 2013 | Burlingame, California, United States
Computational Imaging X
23 January 2012 | Burlingame, California, United States
Computational Imaging VIII
18 January 2010 | San Jose, California, United States
Computational Imaging VII
19 January 2009 | San Jose, California, United States
Computational Imaging VI
28 January 2008 | San Jose, California, United States
Showing 5 of 10 Conference Committees
Course Instructor
SC754: Human Shape Perception
Shape recognition plays a central role in object recognition and while a large number of technical papers on shape representation and similarity exist, shape recognition still remains an unsolved problem. The main goal of this course is to present results on human shape perception, including 2D as well as 3D shape representation and similarity. This course will provide needed background knowledge about important features of shape recognition from the point of view of human visual perception. It will include a tutorial about human shape perception with an emphasis on the most important psychophysical experiments on shape recognition and reconstruction that have been performed during the last 100 years, as well as on computational models of human shape perception. The course will also include an overview of computational approaches to shape similarity and to shape-based retrieval in multimedia databases. We will report an experimental evaluation of their performance on the dataset used in MPEG-7 Core Experiment CE-Shape-1. This dataset provides a unique opportunity to compare various shape descriptors.
SIGN IN TO:
  • View contact details

UPDATE YOUR PROFILE
Is this your profile? Update it now.
Don’t have a profile and want one?

Advertisement
Advertisement
Back to Top