Marcia Riley

18 papers receiving 800 citations

Peers

Marcia Riley
Comparison fields: 5 of 78
  • Control and Systems Engineering 633
  • Biomedical Engineering 399
  • Computer Vision and Pattern Recognition 318
  • Cognitive Neuroscience 131
  • Artificial Intelligence 116
Replace Pedram Azad with:
Pedram Azad Germany
Staffan Ekvall Sweden
F. Guenter Switzerland
Eric L. Sauser Switzerland
Koichi Ogawara Japan
Jim Mainprice United States
Joshua G. Hale Japan
Karinne Ramírez-Amaro Germany
R.O. Ambrose United States
P. Azad Germany
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Countries citing papers authored by Marcia Riley

Since Specialization
Citations

This map shows the geographic impact of Marcia Riley'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 Marcia Riley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcia Riley more than expected).

Fields of papers citing papers by Marcia Riley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcia Riley. 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 Marcia Riley. The network helps show where Marcia Riley may publish in the future.

Co-authorship network of co-authors of Marcia Riley

This figure shows the co-authorship network connecting the top 25 collaborators of Marcia Riley. A scholar is included among the top collaborators of Marcia Riley 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 Marcia Riley. Marcia Riley is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 3
2 5
3 3
4
Building Speaker-Specific Lip Models for Talking Heads from {3D} Face Data
2
5
Are virtual humans uncanny? : varying speech, appearance and motion to better understand the acceptability of synthetic humans
2
6 12
7 18
8 3
9 121
10 61
11 226
12 5
13 58
14 63
15
Methods for Motion Generation and Interaction with a Humanoid Robot: Case Studies of Dancing and Catching
45
16 201
17
Automatic Generation of Kinematic Models for the Conversion of Human Motion Capture Data into Humanoid Robot Motion
32
18 7

About Marcia Riley

Marcia Riley is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Developmental Biology, having authored 18 papers that have together received 867 indexed citations. Recurring topics across this work include Human Motion and Animation (9 papers), Human Pose and Action Recognition (8 papers) and Robot Manipulation and Learning (7 papers). The work is most often cited by research in Control and Systems Engineering (633 citations), Human-Computer Interaction (102 citations) and Computer Vision and Pattern Recognition (318 citations). Marcia Riley has collaborated with scholars based in Japan, United States and Slovenia. Frequent co-authors include Christopher G. Atkeson, Aleš Ude, Nancy S. Pollard, Jessica K. Hodgins, Frank Pollick, Joshua G. Hale, Shinya Kotosaka, Sethu Vijayakumar, Tomohiro Shibata and Mitsuo Kawato. Their work appears in journals such as Biochemistry, Robotics and Autonomous Systems and Autonomous Robots.

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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