Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Jack Y. Jau

dblp:90/4152 · DBLP profile ↗
← Back
3ranked-venue papers
3as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-authorArtificial intelligence and machine learning · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 56% Computational photography and imaging · 44%
Artificial intelligence
1 paper
3D vision · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
surface normal estimation
0.011988
Shape from texture using the Wigner distribution · CVPR 1988
Computational photography and imaging › shape and reflectance estimation
shape from texture
0.011988
Shape from texture using the Wigner distribution · CVPR 1988
Image and video processing
texture analysis
0.011988
Shape from texture using the Wigner distribution · CVPR 1988

Methods — techniques the papers use, named apart from their topics

wigner distribution · 0.0space-frequency representation · 0.0
YearPublicationVenuePosition
1990 Shape from texture using the Wigner distribution
Jack Y. Jau, Roland T. Chin
Comput. Vis. Graph. Image Process.1
1990 Shape from texture using the Wigner distribution
Jack Y. Jau, Roland T. Chin
Comput. Vis. Graph. Image Process.1
1988 Shape from texture using the Wigner distribution
abstract
A method is presented for estimating the orientation of a textured surface as a descriptor of surface shape. It is based on the analysis of local spectrum information of the texture in an image. The local spectrum representation is computed by the two-dimensional Wigner distribution, which gives the spatial-frequency information as a function of location. The change in texture density, or the so-called texture gradient, caused by the perspective projection of a surface in the three dimensional world onto the two-dimensional image plane, is computed from this space-frequency representation by measuring the high-frequency energy distribution at each location of the image. The surface orientation is then estimated from the texture gradient. This method was implemented for the limited case of planar surfaces. Simulations were performed and results were analyzed to address issues related to the method's estimation accuracy, implementation, and limitations.>
Jack Y. Jau, Roland T. Chin
CVPR1