Skip to main content

Detectability of Moving Objects Using Correspondences over Two and Three Frames

  • Conference paper
Book cover Pattern Recognition (DAGM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4713))

Included in the following conference series:

Abstract

The detection of moving objects is crucial for robot navigation and driver assistance systems. In this paper the detectability of moving objects is studied. To this end, image correspondences over two and three frames are considered whereas the images are acquired by a moving monocular camera. The detection is based on the constraints linked to static 3D points. These constraints (epipolar, positive depth, positive height, and trifocal constraint) are discussed briefly, and an algorithm incorporating all of them is proposed. The individual constraints differ in their action depending on the motion of the object. Thus, the detectability of a moving object is influenced by its motion. Three types of motions are investigated: parallel, lateral, and circular motion. The study of the detection limits is applied to real imagery.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Armangué, X., Araújo, H., Salvi, J.: Differential Epipolar Constraint in Mobile Robot Egomotion Estimation. In: IEEE International Conference on Pattern Recognition (ICPR), Québec, Canada, pp. 599–602 (2002)

    Google Scholar 

  2. Hartley, R., Zisserman, A.: Multiple View Geometry in computer vision, 2nd edn. Cambridge Press (2003)

    Google Scholar 

  3. Ke, Q., Kanade, T.: Transforming Camera Geometry to A Virtual Downward-Looking Camera: Robust Ego-Motion Estimation and Ground-Layer Detection. In: IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Madison, USA, pp. I-390- I-397 (2003)

    Google Scholar 

  4. Klappstein, J., Stein, F., Franke, U.: Flussbasierte Eigenbewegungsschätzung und Detektion von fremdbewegten Objekten. In: Workshop Fahrerassistenzsysteme (FAS), Löwenstein, Germany, pp. 78–88 (2006)

    Google Scholar 

  5. Klappstein, J., Stein, F., Franke, U.: Monocular Motion Detection Using Spatial Constraints in a Unified Manner. In: IEEE Intelligent Vehicles Symposium (IV), Tokyo, Japan, pp. 261–266 (2006)

    Google Scholar 

  6. Klappstein, J., Stein, F., Franke, U.: Applying Kalman Filtering to Road Homography Estimation. In: Workshop on Planning, Perception and Navigation for Intelligent Vehicles in conjunction with IEEE International Conference on Robotics and Automation (ICRA), Rome, Italy (2007)

    Google Scholar 

  7. Nistér, D.: An efficient solution to the five-point relative pose problem. In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), June 2004, pp. 756–770 (2004)

    Google Scholar 

  8. Torr, P.H.S., Zisserman, A., Murray, D.W.: Motion Clustering using the Trilinear Constraint over Three Views. In: Mohr, R., Wu, C. (eds.) Europe-China Workshop on Geometrical Modelling and Invariants for Computer Vision, pp. 118–125. Xidan University Press/Springer–Verlag (1995)

    Google Scholar 

  9. Trautwein, S., Mühlich, M., Feiden, D., Mester, R.: Estimating Consistent Motion From Three Views: An Alternative To Trifocal Analysis. In: International Conference on the Analysis of Images and Patterns (CAIP), Ljubljana, Slovenia, pp. 311–320 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Fred A. Hamprecht Christoph Schnörr Bernd Jähne

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Klappstein, J., Stein, F., Franke, U. (2007). Detectability of Moving Objects Using Correspondences over Two and Three Frames. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds) Pattern Recognition. DAGM 2007. Lecture Notes in Computer Science, vol 4713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74936-3_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74936-3_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74933-2

  • Online ISBN: 978-3-540-74936-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics