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Stephen A. Underwood

dblp:04/4675 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1975
—ORCID · none

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

Systems, architecture and hardware · 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.

Artificial intelligence
1 paper
3D vision · 70% Image recognition and object detection · 30%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d reconstruction
0.011975
Visual Learning from Multiple Views · IEEE Trans. Computers 1975
Computer vision › Image recognition and object detection
object recognition
0.011975
Visual Learning from Multiple Views · IEEE Trans. Computers 1975
Computer vision › 3D vision › 3d object recognition
view-based object recognition
0.011975
Visual Learning from Multiple Views · IEEE Trans. Computers 1975
Computer vision › 3D vision › object representation
3d object description
0.011975
Visual Learning from Multiple Views · IEEE Trans. Computers 1975

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

feature mapping · 0.0
YearPublicationVenuePosition
1975 Visual Learning from Multiple Views
abstract
An algorithm is presented in which a computer is visually shown a sequence of views of a solid planar object as the object is rotated in space. The computer automatically forms a three-dimensional description of the object. The description consists of a deterministic description of the object's surfaces and how they are interconnected to form the object, along with a measure of each surface's shape which is invariant to three-dimensional rotation. From this self-learned model of the object, the object can later be recognized from any viewing angle. The basis of the algorithm is the ability of the program to determine in a specific visual view: "What do I see now that I have seen before?" This is accomplished by generating two sets of mappings of one object description to another object description.
Stephen A. Underwood, Clarence L. Coates
IEEE Trans. Computers1