Pose tracking from natural features on mobile phones
Impact in
Classified as
- Journal
- Cambridge University Engineering Department Publications Database
In The Last Decade
doi.org/10.1109/ismar.2008.4637338 →Countries where authors are citing Pose tracking from natural features on mobile phones
This map shows the geographic impact of Pose tracking from natural features on mobile phones. 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 Pose tracking from natural features on mobile phones with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pose tracking from natural features on mobile phones more than expected).
Fields of papers citing Pose tracking from natural features on mobile phones
This network shows the impact of Pose tracking from natural features on mobile phones. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Pose tracking from natural features on mobile phones.
About Pose tracking from natural features on mobile phones
This paper, published in 2008, received 325 indexed citations . Written by Daniel Wägner, Gerhard Reitmayr, Alessandro Mulloni, Tom W. Drummond and Dieter Schmalstieg covering the research area of Computer Vision and Pattern Recognition and Aerospace Engineering. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (307 citations), Aerospace Engineering (212 citations), Human-Computer Interaction (69 citations), Geology (32 citations) and Control and Systems Engineering (21 citations). Published in Cambridge University Engineering Department Publications Database.
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.
This paper is also available at doi.org/10.1109/ismar.2008.4637338.