Peter Carr
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- Video Analysis and Summarization 14
- Human Pose and Action Recognition 10
- Video Surveillance and Tracking Methods 9
- Advanced Vision and Imaging 9
- Face recognition and analysis 5
- Automotive Engineering top 1%
- Signal Processing top 2%
- Time Series Analysis and Forecasting 11
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- Anomaly Detection Techniques and Applications 12
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- Sports Analytics and Performance 12
- Co-authors
- Sławomir BąkIain MatthewsPatrick LuceyJames HaysAndrew T. HartnettJagjeet SinghDeva RamananJohn Lambert
- Journals
- Computer Vision and Image Understanding (2 papers)BMC Bioinformatics (1 paper)IEEE Transactions on Circuits and Systems for Video Technology (1 paper)
- Partner nations
- United StatesAustraliaCanada
In The Last Decade
Peter Carr
51 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Computer Vision and Pattern Recognition 1.3k
- Automotive Engineering 623
- Signal Processing 287
- Orthopedics and Sports Medicine 203
- Safety, Risk, Reliability and Quality 154
Countries citing papers authored by Peter Carr
This map shows the geographic impact of Peter Carr'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 Peter Carr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Carr more than expected).
Fields of papers citing papers by Peter Carr
This network shows the impact of papers produced by Peter Carr. 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 Peter Carr. The network helps show where Peter Carr may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter Carr, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 45 | |
| 2 | 2021 | 5 | |
| 3 | 2021 | 6 | |
| 4 | 2017 | 2 | |
| 5 | DATA-DRIVEN GHOSTING USING DEEP IMITATION LEARNING | 2017 | 23 |
| 6 | 2017 | 9 | |
| 7 | 2016 | 15 | |
| 8 | 2015 | 19 | |
| 9 | 2015 | 22 | |
| 10 | Autonomous Camera Systems: A Survey. | 2014 | 8 |
| 11 | Win at home and draw away: automatic formation analysis highlighting the differences in home and away team behaviors | 2014 | 31 |
| 12 | 2013 | 62 | |
| 13 | 2013 | 11 | |
| 14 | 2013 | 43 | |
| 15 | Characterizing multi-agent team behavior from partial team tracings: evidence from the english premier league | 2012 | 19 |
| 16 | 2009 | 10 | |
| 17 | 2009 | 10 | |
| 18 | 2009 | 52 | |
| 19 | 2005 | 2 | |
| 20 | 2004 | 2 |
About Peter Carr
Peter Carr is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 51 papers that have together received 2.1k indexed citations. Recurring topics across this work include Video Analysis and Summarization (14 papers), Anomaly Detection Techniques and Applications (12 papers), Sports Analytics and Performance (12 papers), Time Series Analysis and Forecasting (11 papers), Human Pose and Action Recognition (10 papers), Video Surveillance and Tracking Methods (9 papers), Advanced Vision and Imaging (9 papers) and Face recognition and analysis (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Automotive Engineering (623 citations) and Signal Processing (287 citations). Peter Carr has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Sławomir Bąk, Iain Matthews, Patrick Lucey, James Hays, Andrew T. Hartnett, Jagjeet Singh, Deva Ramanan, John Lambert, Simon Lucey and Ming-Fang Chang. Their work appears in journals such as Computer Vision and Image Understanding, BMC Bioinformatics, IEEE Transactions on Circuits and Systems for Video Technology, Journal of Supply Chain Management and IEEE Transactions on Affective Computing.
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.