Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ivaturi S. N. Murthy
dblp:72/1843
· DBLP profile ↗
4ranked-venue papers
1as first author
0since 2021 · last 1977
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1
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 |
Geometric modeling and processing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing
shape analysis |
0.0 | 1 | 1977 | New Concepts for Three-Dimensional Shape Analysis · IEEE Trans. Computers 1977 |
Geometric modeling and processing
shape matching |
0.0 | 1 | 1977 | New Concepts for Three-Dimensional Shape Analysis · IEEE Trans. Computers 1977 |
Geometric modeling and processing › spatial reasoning › geometric reasoning
line drawing interpretation |
0.0 | 1 | 1977 | New Concepts for Three-Dimensional Shape Analysis · IEEE Trans. Computers 1977 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1977 | New Concepts for Three-Dimensional Shape AnalysisabstractA new approach to machine representation and analysis of three-dimensional objects is presented. The representation, based on the notion of "skeleton" of an object leads to a scheme for comparing two given object views for shape relations. The objects are composed of long, thin, rectangular prisms joined at their ends. The input picture to the program is the digitized line drawing portraying the three-dimensional object. To compare two object views, two characteristic vertices called "cardinal point" and "end-cardinal point," occurring consistently at the bends and open ends of the object are detected. The skeletons are then obtained as a connected path passing through these points. The shape relationships between the objects are then obtained from the matching characteristics of their skeletons. The method explores the possibility of a more detailed and finer analysis leading to detection of features like symmetry, asymmetry and other shape properties of an object. Jayaram K. Udupa, Ivaturi S. N. Murthy |
IEEE Trans. Computers | 2 |
| 1977 | Machine Visualization of Three-Dimensional Objects via Skeletal TransformationsabstractComputer simulation of one aspect of the human visual perceptual capabilities, viz., the ability to visualize object views that result from known rotations of familiar objects is considered. The objects considered are composed of long, thin, and narrow rectangular prisms connected at their ends. From the digitized binary picture of the line drawing portraying a given three-dimensional object a description is generated in terms of a set of "cardinal points" (which are key points occurring at the bends and open ends of the object) and a set of direction vectors associated with them. The skeleton for the given view is obtained as an ordered sequence of "slope-code" numbers by tracking between the cardinal points. A set of transformations is defined on the sequence and the direction vectors to get the skeleton of the view that results from rotation. From a knowledge of the transformed direction vectors the machine builds up faces around the bends and ends of the skeleton to complete the new view. As far as machine visualization is concerned, it is shown that object rotations of only integer multiples of π/2 need be considered. Jayaram K. Udupa, Ivaturi S. N. Murthy |
IEEE Trans. Syst. Man Cybern. | 2 |
| 1975 | Some new concepts for encoding line patterns
Jayaram K. Udupa, Ivaturi S. N. Murthy |
Pattern Recognit. | 2 |
| 1974 | A search algorithm for skeletonization of thick patterns
Ivaturi S. N. Murthy, Jayaram K. Udupa |
Comput. Graph. Image Process. | 1 |