Olaf Kähler

1.2k total citations
18 papers, 604 citations indexed

About

Olaf Kähler is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Environmental Engineering. According to data from OpenAlex, Olaf Kähler has authored 18 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 14 papers in Aerospace Engineering and 4 papers in Environmental Engineering. Recurrent topics in Olaf Kähler's work include Robotics and Sensor-Based Localization (14 papers), Advanced Vision and Imaging (12 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Olaf Kähler is often cited by papers focused on Robotics and Sensor-Based Localization (14 papers), Advanced Vision and Imaging (12 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Olaf Kähler collaborates with scholars based in United Kingdom, Germany and Australia. Olaf Kähler's co-authors include David W. Murray, Victor Adrian Prisacariu, Philip H. S. Torr, Carl Yuheng Ren, Xin Sun, Ian Reid, Joachim Denzler, Vibhav Vineet, Ondřej Mikšík and Shahram Izadi and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Vision.

In The Last Decade

Olaf Kähler

17 papers receiving 590 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Olaf Kähler United Kingdom 11 480 420 196 77 47 18 604
Haoang Li Hong Kong 12 404 0.8× 427 1.0× 216 1.1× 97 1.3× 83 1.8× 36 605
Bernhard Zeisl Switzerland 9 449 0.9× 405 1.0× 184 0.9× 102 1.3× 54 1.1× 14 657
Michal Havlena Switzerland 12 567 1.2× 434 1.0× 181 0.9× 95 1.2× 23 0.5× 28 755
John McCormac United Kingdom 3 613 1.3× 540 1.3× 220 1.1× 82 1.1× 79 1.7× 3 777
Jorge Fuentes-Pacheco Mexico 5 454 0.9× 456 1.1× 119 0.6× 58 0.8× 24 0.5× 12 671
Shi-Sheng Huang China 13 407 0.8× 295 0.7× 222 1.1× 115 1.5× 140 3.0× 20 621
Chin Seng Chua Singapore 7 495 1.0× 361 0.9× 181 0.9× 41 0.5× 187 4.0× 12 641
S.W. Lee South Korea 5 385 0.8× 390 0.9× 207 1.1× 106 1.4× 119 2.5× 7 575
Srikumar Ramalingam United States 15 574 1.2× 567 1.4× 310 1.6× 124 1.6× 143 3.0× 23 851
Stefan May Germany 13 313 0.7× 308 0.7× 143 0.7× 126 1.6× 17 0.4× 48 620

Countries citing papers authored by Olaf Kähler

Since Specialization
Citations

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

Fields of papers citing papers by Olaf Kähler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olaf Kähler

This figure shows the co-authorship network connecting the top 25 collaborators of Olaf Kähler. A scholar is included among the top collaborators of Olaf Kähler 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 Olaf Kähler. Olaf Kähler 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
1.
Kähler, Olaf, et al.. (2021). A Comparison of Deep Learning Methods for Airborne Lidar Point Clouds Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 6467–6486. 28 indexed citations
2.
Otepka, Johannes, Norbert Pfeifer, Michael Hornáček, et al.. (2020). Generalized Sparse Convolutional Neural Networks for Semantic Segmentation of Point Clouds Derived from Tri-Stereo Satellite Imagery. Remote Sensing. 12(8). 1289–1289. 11 indexed citations
3.
Kähler, Olaf, et al.. (2020). AUTOMATING POWERLINE INSPECTION: A NOVEL MULTISENSOR SYSTEM FOR DATA ANALYSIS USING DEEP LEARNING. SHILAP Revista de lepidopterología. XLIII-B4-2020. 747–754. 12 indexed citations
4.
Ren, Carl Yuheng, Victor Adrian Prisacariu, Olaf Kähler, Ian Reid, & David W. Murray. (2017). Real-Time Tracking of Single and Multiple Objects from Depth-Colour Imagery Using 3D Signed Distance Functions. International Journal of Computer Vision. 124(1). 80–95. 23 indexed citations
5.
Kähler, Olaf, et al.. (2016). Object-aware bundle adjustment for correcting monocular scale drift. 4770–4776. 38 indexed citations
6.
Vineet, Vibhav, Ondřej Mikšík, Matthias NieBner, et al.. (2015). Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction. 75–82. 131 indexed citations
7.
Golodetz, Stuart, Michael Sapienza, Vibhav Vineet, et al.. (2015). SemanticPaint. 1–1. 6 indexed citations
8.
Kähler, Olaf, Victor Adrian Prisacariu, Julien Valentin, & David W. Murray. (2015). Hierarchical Voxel Block Hashing for Efficient Integration of Depth Images. IEEE Robotics and Automation Letters. 1(1). 192–197. 44 indexed citations
9.
Kähler, Olaf, Victor Adrian Prisacariu, Carl Yuheng Ren, et al.. (2015). Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices. IEEE Transactions on Visualization and Computer Graphics. 21(11). 1241–1250. 200 indexed citations
10.
Prisacariu, Victor Adrian, Olaf Kähler, David W. Murray, & Ian Reid. (2014). Real-Time 3D Tracking and Reconstruction on Mobile Phones. IEEE Transactions on Visualization and Computer Graphics. 21(5). 557–570. 28 indexed citations
11.
Kähler, Olaf & Ian Reid. (2013). Efficient 3D Scene Labeling Using Fields of Trees. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 3064–3071. 28 indexed citations
12.
Prisacariu, Victor Adrian, Olaf Kähler, David W. Murray, & Ian Reid. (2013). Simultaneous 3D tracking and reconstruction on a mobile phone. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 89–98. 21 indexed citations
13.
Kähler, Olaf & Joachim Denzler. (2011). Tracking and Reconstruction in a Combined Optimization Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(2). 387–401. 5 indexed citations
14.
Kähler, Olaf & Joachim Denzler. (2008). Robust Real-Time SFM in a Combined Formulation of Tracking and Reconstruction.. Vision Modeling and Visualization. 283–292. 1 indexed citations
15.
Kähler, Olaf, Erik Rodner, & Joachim Denzler. (2008). On fusion of range and intensity information using Graph-Cut for planar patch segmentation. International Journal of Intelligent Systems Technologies and Applications. 5(3/4). 365–365. 10 indexed citations
16.
Kähler, Olaf & Joachim Denzler. (2007). DETECTING COPLANAR FEATURE POINTS IN HANDHELD IMAGE SEQUENCES. 447–452. 7 indexed citations
17.
Kähler, Olaf & Joachim Denzler. (2005). Self-Organizing, Adaptive Data Fusion for 3d Object Tracking.. 33(6). 109–116. 1 indexed citations
18.
Kähler, Olaf, Joachim Denzler, & Jochen Triesch. (2004). Hierarchical sensor data fusion by probabilistic cue integration for robust 3D object tracking. 216–220. 10 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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