Ido Leichter
- Computer Vision and Pattern Recognition top 2%
- Human-Computer Interaction top 1%
- Control and Systems Engineering top 10%
- Aerospace Engineering top 10%
- Artificial Intelligence
- Co-authors
- Michael LindenbaumEhud RivlinEyal KrupkaAlon VinnikovDaniel Z. FreedmanDavid KimChristoph RhemannJamie Shotton
- Topics
- Video Surveillance and Tracking Methods (12 papers)Advanced Vision and Imaging (8 papers)Advanced Image and Video Retrieval Techniques (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionComputer Vision and Image Understanding
- Partner nations
- IsraelUnited StatesUnited Kingdom
In The Last Decade
Ido Leichter
17 papers receiving 693 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Computer Vision and Pattern Recognition 561
- Human-Computer Interaction 259
- Control and Systems Engineering 116
- Aerospace Engineering 113
- Artificial Intelligence 80
Countries citing papers authored by Ido Leichter
This map shows the geographic impact of Ido Leichter'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 Ido Leichter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ido Leichter more than expected).
Fields of papers citing papers by Ido Leichter
This network shows the impact of papers produced by Ido Leichter. 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 Ido Leichter. The network helps show where Ido Leichter may publish in the future.
Co-authorship network of co-authors of Ido Leichter
This figure shows the co-authorship network connecting the top 25 collaborators of Ido Leichter. A scholar is included among the top collaborators of Ido Leichter 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 Ido Leichter. Ido Leichter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 15 | |
| 3 | Accurate, Robust, and Flexible Real-time Hand Trackingbreakdown → | 285 |
| 4 | 12 | |
| 5 | 6 | |
| 6 | 56 | |
| 7 | 1 | |
| 8 | 87 | |
| 9 | 0 | |
| 10 | 6 | |
| 11 | 2009 IEEE 12th International Conference on Computer Vision (ICCV) | 121 |
| 12 | 19 | |
| 13 | 43 | |
| 14 | 7 | |
| 15 | 6 | |
| 16 | 18 | |
| 17 | 1 | |
| 18 | 32 |
About Ido Leichter
Ido Leichter is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 18 papers that have together received 718 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (12 papers), Advanced Vision and Imaging (8 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Human-Computer Interaction (259 citations), Computer Vision and Pattern Recognition (561 citations) and Media Technology (47 citations). Ido Leichter has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Michael Lindenbaum, Ehud Rivlin, Eyal Krupka, Alon Vinnikov, Daniel Z. Freedman, David Kim, Christoph Rhemann, Jamie Shotton, Cem Keskin and Shahram Izadi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Computer Vision and Image Understanding.
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.