A Quaternion Sign Can Change a Naive Midpoint Without Changing Either Endpoint Pose

Authors

  • Cameron Porter Author
  • Jack Brooks Author
  • James Harrison Author

Abstract

Two quaternions with opposite signs encode the same rotation, yet their component average can behave very differently. We examined 615,364 short-interval pose pairs in 52 TUM RGB-D files. Native endpoint signs caused 778 naive normalized midpoints to be undefined or more than one degree from the shortest-path midpoint. The equal-file failure fraction was 0.1732%. Aligning endpoint hemispheres before averaging reduced the maximum observed midpoint discrepancy to numerical precision. This is a representation-consistency result for two-pose midpoints, not a test of physical intermediate orientation or a learned motion model.

Representation audit of native camera quaternions. The deliberately naive midpoint is our comparison rule; native sign choices are valid rotation representations and are not labelled dataset errors.

Original publication: October 28, 2026.

References

  1. Zhang, Zichao; Scaramuzza, Davide. (2018). A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/IROS.2018.8593941.
  2. Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; Axton, Myles; Baak, Arie; Blomberg, Niklas; Boiten, Jan-Willem; da Silva Santos, Luiz Bonino; Bourne, Philip E.; Bouwman, Jildau; Brookes, Anthony J.; Clark, Tim; Crosas, Mercè; Dillo, Ingrid; Dumon, Olivier; Edmunds, Scott; Evelo, Chris T.; Finkers, Richard; Gonzalez-Beltran, Alejandra; Gray, Alasdair J.G.; Groth, Paul; Goble, Carole; Grethe, Jeffrey S.; Heringa, Jaap; ’t Hoen, Peter A.C; Hooft, Rob; Kuhn, Tobias; Kok, Ruben; Kok, Joost; Lusher, Scott J.; Martone, Maryann E.; Mons, Albert; Packer, Abel L.; Persson, Bengt; Rocca-Serra, Philippe; Roos, Marco; van Schaik, Rene; Sansone, Susanna-Assunta; Schultes, Erik; Sengstag, Thierry; Slater, Ted; Strawn, George; Swertz, Morris A.; Thompson, Mark; van der Lei, Johan; van Mulligen, Erik; Velterop, Jan; Waagmeester, Andra; Wittenburg, Peter; Wolstencroft, Katherine; Zhao, Jun; Mons, Barend. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. https://doi.org/10.1038/sdata.2016.18.
  3. Gebru, Timnit, et al. "Datasheets for datasets" Communications of the ACM, 2021. https://doi.org/10.1145/3458723.
  4. Dosovitskiy, Alexey; Ros, German; Codevilla, Felipe; Lopez, Antonio; Koltun, Vladlen. (2017). CARLA: An Open Urban Driving Simulator. arXiv:1711.03938. https://arxiv.org/abs/1711.03938.
  5. Stevens, S. S.. (1946). On the Theory of Scales of Measurement. Science. https://doi.org/10.1126/science.103.2684.677.
  6. Cook, R. Dennis. (1977). Detection of Influential Observation in Linear Regression. Technometrics. https://doi.org/10.1080/00401706.1977.10489493.
  7. Meng, Zijie. (2026). OrthoMotion:Disentangling Camera and Subject Motion via Geometry Semantics Orthogonal Attention. arXiv:2606.22835. https://arxiv.org/abs/2606.22835.
  8. Burri, Michael; Nikolic, Janosch; Gohl, Pascal; Schneider, Thomas; Rehder, Joern; Omari, Sammy; Achtelik, Markus W; Siegwart, Roland. (2016). The EuRoC micro aerial vehicle datasets. The International Journal of Robotics Research. https://doi.org/10.1177/0278364915620033.
  9. Virtanen, Pauli; Gommers, Ralf; Oliphant, Travis E.; Haberland, Matt; Reddy, Tyler; Cournapeau, David; Burovski, Evgeni; Peterson, Pearu; Weckesser, Warren; Bright, Jonathan; van der Walt, Stéfan J.; Brett, Matthew; Wilson, Joshua; Millman, K. Jarrod; Mayorov, Nikolay; Nelson, Andrew R. J.; Jones, Eric; Kern, Robert; Larson, Eric; Carey, C J; Polat, İlhan; Feng, Yu; Moore, Eric W.; VanderPlas, Jake; Laxalde, Denis; Perktold, Josef; Cimrman, Robert; Henriksen, Ian; Quintero, E. A.; Harris, Charles R.; Archibald, Anne M.; Ribeiro, Antônio H.; Pedregosa, Fabian; van Mulbregt, Paul; SciPy 1.0 Contributors; Vijaykumar, Aditya; Bardelli, Alessandro Pietro; Rothberg, Alex; Hilboll, Andreas; Kloeckner, Andreas; Scopatz, Anthony; Lee, Antony; Rokem, Ariel; Woods, C. Nathan; Fulton, Chad; Masson, Charles; Häggström, Christian; Fitzgerald, Clark; Nicholson, David A.; Hagen, David R.; Pasechnik, Dmitrii V.; Olivetti, Emanuele; Martin, Eric; Wieser, Eric; Silva, Fabrice; Lenders, Felix; Wilhelm, Florian; Young, G.; Price, Gavin A.; Ingold, Gert-Ludwig; Allen, Gregory E.; Lee, Gregory R.; Audren, Hervé; Probst, Irvin; Dietrich, Jörg P.; Silterra, Jacob; Webber, James T; Slavič, Janko; Nothman, Joel; Buchner, Johannes; Kulick, Johannes; Schönberger, Johannes L.; de Miranda Cardoso, José Vinícius; Reimer, Joscha; Harrington, Joseph; Rodríguez, Juan Luis Cano; Nunez-Iglesias, Juan; Kuczynski, Justin; Tritz, Kevin; Thoma, Martin; Newville, Matthew; Kümmerer, Matthias; Bolingbroke, Maximilian; Tartre, Michael; Pak, Mikhail; Smith, Nathaniel J.; Nowaczyk, Nikolai; Shebanov, Nikolay; Pavlyk, Oleksandr; Brodtkorb, Per A.; Lee, Perry; McGibbon, Robert T.; Feldbauer, Roman; Lewis, Sam; Tygier, Sam; Sievert, Scott; Vigna, Sebastiano; Peterson, Stefan; More, Surhud; Pudlik, Tadeusz; Oshima, Takuya; Pingel, Thomas J.; Robitaille, Thomas P.; Spura, Thomas; Jones, Thouis R.; Cera, Tim; Leslie, Tim; Zito, Tiziano; Krauss, Tom; Upadhyay, Utkarsh; Halchenko, Yaroslav O.; Vázquez-Baeza, Yoshiki. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods. https://doi.org/10.1038/s41592-019-0686-2.
  10. SciPy developers. (2026). scipy.spatial.transform.Slerp [API documentation; snapshot accessed 7 November 2026]. https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.transform.Slerp.html.
  11. Schubert, David; Goll, Thore; Demmel, Nikolaus; Usenko, Vladyslav; Stückler, Jörg; Cremers, Daniel. (2018). The TUM VI Benchmark for Evaluating Visual-Inertial Odometry. arXiv:1804.06120. https://arxiv.org/abs/1804.06120.
  12. Blanco-Claraco, José Luis. (2021). A tutorial on SE(3) transformation parameterizations and on-manifold optimization. arXiv:2103.15980; arXivversionyear, originaltechnicalreport2010. https://arxiv.org/abs/2103.15980.
  13. Hartley, Richard; Trumpf, Jochen; Dai, Yuchao; Li, Hongdong. (2013). Rotation Averaging. International Journal of Computer Vision. https://doi.org/10.1007/s11263-012-0601-0.
  14. Cameron, A. Colin, and Douglas L. Miller. “A Practitioner’s Guide to Cluster-Robust Inference.” Journal of Human Resources, vol. 50, no. 2, 2015, pp. 317-372. https://doi.org/10.3368/jhr.50.2.317.
  15. Yohann, Cabon,; Naila, Murray,; Martin, Humenberger,. (2020). Virtual KITTI 2. https://arxiv.org/abs/2001.10773.
  16. Shoemake, Ken. (1985). Animating rotation with quaternion curves. Proceedings of the 12th annual conference on Computer graphics and interactive techniques - SIGGRAPH '85. https://doi.org/10.1145/325334.325242.
  17. TUM Computer Vision Group. (2026). RGB-D SLAM Dataset: File Formats [Official documentation; accessed8November2026, captureyearnotbenchmarkyear]. https://cvg.cit.tum.de/data/datasets/rgbd-dataset/file_formats.
  18. Geiger, A.; Lenz, P.; Urtasun, R.. (2012). Are we ready for autonomous driving? The KITTI vision benchmark suite. 2012 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2012.6248074.
  19. Huber, Peter J.. (1964). Robust Estimation of a Location Parameter. The Annals of Mathematical Statistics. https://doi.org/10.1214/aoms/1177703732.
  20. Carroll, Raymond J., David Ruppert, Leonard A. Stefanski, and Ciprian M. Crainiceanu. “Measurement Error in Nonlinear Models.” 2006. https://doi.org/10.1201/9781420010138.
  21. Hartley, Richard; Zisserman, Andrew. (2004). Multiple View Geometry in Computer Vision. Cambridge University Press. https://doi.org/10.1017/cbo9780511811685.
  22. Sturm, Jürgen; Engelhard, Nikolas; Endres, Felix; Burgard, Wolfram; Cremers, Daniel. (2012). A benchmark for the evaluation of RGB-D SLAM systems. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/IROS.2012.6385773.
  23. Markley, F. Landis; Cheng, Yang; Crassidis, John L.; Oshman, Yaakov. (2007). Averaging Quaternions. Journal of Guidance, Control, and Dynamics. https://doi.org/10.2514/1.28949.
  24. Barfoot, Timothy D.. (2017). State Estimation for Robotics. Cambridge University Press, first edition. https://doi.org/10.1017/9781316671528.
  25. Goldberg, David. (1991). What every computer scientist should know about floating-point arithmetic. ACM Computing Surveys. https://doi.org/10.1145/103162.103163.
  26. White, Halbert. “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica, vol. 48, no. 4, 1980, pp. 817-838. https://doi.org/10.2307/1912934.
  27. Grassia, F. Sebastian. (1998). Practical Parameterization of Rotations Using the Exponential Map. Journal of Graphics Tools. https://doi.org/10.1080/10867651.1998.10487493.
  28. Higham, Nicholas J.. (2002). Accuracy and Stability of Numerical Algorithms: Second Edition. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9780898718027.
  29. Huynh, Du Q.. (2009). Metrics for 3D Rotations: Comparison and Analysis. Journal of Mathematical Imaging and Vision. https://doi.org/10.1007/s10851-009-0161-2.
  30. Roberts, David R., et al. “Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure.” Ecography, vol. 40, no. 8, 2017, pp. 913-929. https://doi.org/10.1111/ecog.02881.

Downloads

Published

2026-10-28