Multimodal Vision Research Laboratory

MVRL

Research Area: Camera Calibration

We develop methods for camera calibration and geometric understanding from images. Our research includes structure-aware methods for direct pose estimation, extending absolute pose regression to multiple scenes, and using natural cues like clouds, rainbows, and horizon lines for calibration. Recent work focuses on cross-view pose estimation, stereo matching for depth estimation, and calibration techniques that work with limited or challenging imaging conditions. We also explore calibration methods for webcam networks and time-lapse sequences, enabling accurate geometric understanding from distributed camera systems.

Publications

  1. Xiong Z, Qiao F, Zhang Y, Jacobs N. 2023. StereoFlowGAN: Co-training for Stereo and Flow with Unsupervised Domain Adaptation. In: British Machine Vision Conference (BMVC).
  2. Zhu XX, Wang Y, Kochupillai M, Werner M, Haberle M, Hoffmann EJ, Taubenbock H, Tuia D, Levering A, Jacobs N, Kruspe A, Abdulahhad K. 2022. Geoinformation Harvesting From Social Media Data: A community remote sensing approach. IEEE Geoscience and Remote Sensing Magazine 10:150–180. DOI: 10.1109/MGRS.2022.3219584.
  3. Thumbnail for Content-Based Detection of Temporal Metadata Manipulation
    Padilha R, Salem T, Workman S, Andaló FA, Rocha A, Jacobs N. 2022. Content-Based Detection of Temporal Metadata Manipulation. IEEE Transactions on Information Forensics and Security:1316–1327. DOI: 10.1109/TIFS.2022.3159154.
  4. Thumbnail for A Structure-Aware Method for Direct Pose Estimation
    Blanton H, Workman S, Jacobs N. 2022. A Structure-Aware Method for Direct Pose Estimation. In: IEEE Winter Conference on Applications of Computer Vision (WACV). DOI: 10.1109/WACV51458.2022.00028.
  5. Tuia D, Roscher R, Wegner JD, Jacobs N, Zhu XX, Camps-Valls G. 2021. Towards a Collective Agenda on AI for Earth Science Data Analysis. IEEE Geoscience and Remote Sensing Magazine 9:88–104. DOI: 10.1109/MGRS.2020.3043504.
  6. Blanton H, Greenwell C, Workman S, Jacobs N. 2020. Extending Absolute Pose Regression to Multiple Scenes. In: Joint Workshop on Long-Term Visual Localization, Visual Odometry and Geometric and Learning-based SLAM (CVPR Workshop). DOI: 10.1109/CVPRW50498.2020.00027.
  7. Thumbnail for Detecting Vanishing Points using Global Image Context in a Non-Manhattan World
    Zhai M, Workman S, Jacobs N. 2016. Detecting Vanishing Points using Global Image Context in a Non-Manhattan World. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). DOI: 10.1109/CVPR.2016.610.
  8. Zhai M, Workman S, Jacobs N. 2016. Camera Geo-Calibration using an MCMC Approach. In: IEEE International Conference on Image Processing (ICIP). DOI: 10.1109/ICIP.2016.7532905.
  9. Thumbnail for Horizon Lines in the Wild
    Workman S, Zhai M, Jacobs N. 2016. Horizon Lines in the Wild. In: British Machine Vision Conference (BMVC).
  10. Thumbnail for Scene Shape Estimation from Multiple Partly Cloudy Days
    Workman S, Souvenir R, Jacobs N. 2015. Scene Shape Estimation from Multiple Partly Cloudy Days. Computer Vision and Image Understanding (CVIU):116–129. DOI: 10.1016/j.cviu.2014.10.002.
  11. Workman S, Greenwell C, Zhai M, Baltenberger R, Jacobs N. 2015. DeepFocal: A Method for Direct Focal Length Estimation. In: IEEE International Conference on Image Processing (ICIP). DOI: 10.1109/ICIP.2015.7351024.
  12. Workman S, Jacobs N. 2015. On the Location Dependence of Convolutional Neural Network Features. In: IEEE/ISPRS Workshop: Large Scale Computer Vision for Remote Sensing (EARTHVISION). 1–9. DOI: 10.1109/CVPRW.2015.7301385.
  13. Thumbnail for A Pot of Gold: Rainbows as a Calibration Cue
    Workman S, Mihail RP, Jacobs N. 2014. A Pot of Gold: Rainbows as a Calibration Cue. In: European Conference on Computer Vision (ECCV). 820–835. DOI: 10.1007/978-3-319-10602-1_53.
  14. Smith JD, Baltenberger R, Workman S, Jacobs N. 2014. User-in-the-Loop Calibration and Mensuration. In: National Conference on Undergraduate Research (NCUR).
  15. Jacobs N, Abrams A, Pless R. 2013. Two Cloud-Based Cues for Estimating Scene Structure and Camera Calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 35:2526–2538. DOI: 10.1109/TPAMI.2013.55.
  16. Thumbnail for Scene Geometry from Several Partly Cloudy Days
    Jacobs N, Workman S, Souvenir R. 2013. Scene Geometry from Several Partly Cloudy Days. In: ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC). 1–6. DOI: 10.1109/ICDSC.2013.6778227.
  17. Thumbnail for Cloud Motion as a Calibration Cue
    Jacobs N, Islam MT, Workman S. 2013. Cloud Motion as a Calibration Cue. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1344–1351. DOI: 10.1109/CVPR.2013.177.
  18. Jacobs N, Miskell K, Pless R. 2011. Webcam Geo-localization using Aggregate Light Levels. In: IEEE Workshop on Applications of Computer Vision (WACV). 132–138. DOI: 10.1109/WACV.2011.5711494.
  19. Thumbnail for Using Cloud Shadows to Infer Scene Structure and Camera Calibration
    Jacobs N, Bies B, Pless R. 2010. Using Cloud Shadows to Infer Scene Structure and Camera Calibration. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1102–1109. DOI: 10.1109/CVPR.2010.5540093.
  20. Jacobs N. 2010. Discovering, Localizing, Calibrating, and Using Thousands of Outdoor Webcams. Computer Science and Engineering, Washington University in St. Louis, MO, USA.
  21. Jacobs N, Schuh S, Pless R. 2010. Compressive Sensing and Differential Image Motion Estimation. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 718–721. DOI: 10.1109/ICASSP.2010.5495053.
  22. Abrams A, Fridrich N, Jacobs N, Pless R. 2010. Participatory Integration of Live Webcams into GIS. In: International Conference on Computing for Geospatial Research and Applications (COM.GEO). 1–8. DOI: 10.1145/1823854.1823867.
  23. Thumbnail for The Global Network of Outdoor Webcams: Properties and Applications
    Jacobs N, Burgin W, Fridrich N, Abrams A, Miskell K, Braswell BH, Richardson AD, Pless R. 2009. The Global Network of Outdoor Webcams: Properties and Applications. In: ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL). 111–120. DOI: 10.1145/1653771.1653789.
  24. Jacobs N, Pless R. 2009. Calibrating and Using the Global Network of Outdoor Webcams. In: ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC). 1–2. DOI: 10.1109/ICDSC.2009.5289404.
  25. Jacobs N, Schuh S, Pless R. 2009. On Unusual Pixel Shapes and Image Motion. Computer Science and Engineering, Washington University in St. Louis, MO, USA.
  26. Jacobs N, Burgin W, Speyer R, Ross D, Pless R. 2009. Adventures in Archiving and Using Three Years of Webcam Images. In: IEEE CVPR Workshop on Internet Vision. 39–46. DOI: 10.1109/CVPRW.2009.5204185.
  27. Jacobs N, Souvenir R, Pless R. 2009. Passive Vision: The Global Webcam Imaging Network. In: IEEE Applied Imagery and Pattern Recognition (AIPR). 1–8. DOI: 10.1109/AIPR.2009.5466314.
  28. Jacobs N, Roman N, Pless R. 2008. Toward Fully Automatic Geo-Location and Geo-Orientation of Static Outdoor Cameras. In: IEEE Workshop on Applications of Computer Vision (WACV). 1–6. DOI: 10.1109/WACV.2008.4544040.
  29. Thumbnail for Geolocating Static Cameras
    Jacobs N, Satkin S, Roman N, Speyer R, Pless R. 2007. Geolocating Static Cameras. In: IEEE International Conference on Computer Vision (ICCV). 1–6. DOI: 10.1109/ICCV.2007.4408995.