Daniel N. Wood

1.2k total citations
4 papers, 622 citations indexed

About

Daniel N. Wood is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Daniel N. Wood has authored 4 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Graphics and Computer-Aided Design, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Computational Mechanics. Recurrent topics in Daniel N. Wood's work include Computer Graphics and Visualization Techniques (3 papers), Advanced Vision and Imaging (2 papers) and 3D Surveying and Cultural Heritage (1 paper). Daniel N. Wood is often cited by papers focused on Computer Graphics and Visualization Techniques (3 papers), Advanced Vision and Imaging (2 papers) and 3D Surveying and Cultural Heritage (1 paper). Daniel N. Wood collaborates with scholars based in United States. Daniel N. Wood's co-authors include David Salesin, Tom Duchamp, Brian Curless, Werner Stuetzle, John F. Hughes, Adam Finkelstein, Cindy Grimm, Brian Guenter and H.S. Malvar and has published in prestigious journals such as .

In The Last Decade

Daniel N. Wood

4 papers receiving 550 citations

Peers

Daniel N. Wood

CVPR

CGCD

CM

CSE

AE

Maryann Simmons United States

Ralf Sarlette Germany

Ken‐ichi Anjyo Japan

Ryota Natsume Japan

Remo Ziegler Switzerland

S. Vedula United States

Matthew Webb United Kingdom

Sergio Orts Escolano United Kingdom

Barbara J. Meier United States

Zhao Dong United States

Maryann Simmons United States

Daniel N. Wood

483 ×0.9

CVPR

281 ×0.7

CGCD

204 ×1.1

CM

58 ×0.8

CSE

23 ×0.5

AE

Citations per year, relative to Daniel N. Wood Daniel N. Wood (= 1×) peers Maryann Simmons

Countries citing papers authored by Daniel N. Wood

Since Specialization

Citations

This map shows the geographic impact of Daniel N. Wood's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel N. Wood with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel N. Wood more than expected).

Fields of papers citing papers by Daniel N. Wood

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel N. Wood. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel N. Wood. The network helps show where Daniel N. Wood may publish in the future.

Co-authorship network of co-authors of Daniel N. Wood

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel N. Wood. A scholar is included among the top collaborators of Daniel N. Wood based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel N. Wood. Daniel N. Wood is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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4 of 4 papers shown

1.

Guenter, Brian, et al.. (2006). Making faces. 18–18. 132 indexed citations

2.

Wood, Daniel N., et al.. (2003). View-dependent refinement of multiresolution meshes with subdivision connectivity. 69–78. 14 indexed citations

3.

Wood, Daniel N., et al.. (2000). Surface light fields for 3D photography. 287–296. 327 indexed citations

4.

Wood, Daniel N., et al.. (1997). Multiperspective panoramas for cel animation. 243–250. 149 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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