Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Finding Trajectories of Feature Points in a Monocular Image Sequence

Published: 01 January 1987 Publication History

Abstract

Identifying the same physical point in more than one image, the correspondence problem, is vital in motion analysis. Most research for establishing correspondence uses only two frames of a sequence to solve this problem. By using a sequence of frames, it is possible to exploit the fact that due to inertia the motion of an object cannot change instantaneously. By using smoothness of motion, it is possible to solve the correspondence problem for arbitrary motion of several nonrigid objects in a scene. We formulate the correspondence problem as an optimization problem and propose an iterative algorithm to find trajectories of points in a monocular image sequence. A modified form of this algorithm is useful in case of occlusion also. We demonstrate the efficacy of this approach considering synthetic, laboratory, and real scenes.

Cited By

View all
  • (2023)CycleNetProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666577(10359-10384)Online publication date: 10-Dec-2023
  • (2021)Visualization of submerged turbulent jets using particle tracking velocimetryJournal of Visualization10.1007/s12650-021-00744-424:4(699-710)Online publication date: 1-Aug-2021
  • (2017)Toward accurate real-time marker labeling for live optical motion captureThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-017-1400-y33:6-8(993-1003)Online publication date: 1-Jun-2017
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence  Volume 9, Issue 1
January 1987
185 pages

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 January 1987

Author Tags

  1. Correspondence
  2. motion object tracking
  3. path coherence
  4. smoothness of motion
  5. structure from motion

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 26 Sep 2024

Other Metrics

Citations

Cited By

View all
  • (2023)CycleNetProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666577(10359-10384)Online publication date: 10-Dec-2023
  • (2021)Visualization of submerged turbulent jets using particle tracking velocimetryJournal of Visualization10.1007/s12650-021-00744-424:4(699-710)Online publication date: 1-Aug-2021
  • (2017)Toward accurate real-time marker labeling for live optical motion captureThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-017-1400-y33:6-8(993-1003)Online publication date: 1-Jun-2017
  • (2015)Polygonal approximation of digital planar curve using local integral deviationInternational Journal of Computational Vision and Robotics10.1504/IJCVR.2015.0713335:3(302-319)Online publication date: 1-Aug-2015
  • (2015)Object tracking based on an online learning network with total error rate minimizationPattern Recognition10.1016/j.patcog.2014.07.02048:1(126-139)Online publication date: 1-Jan-2015
  • (2015)Spatiotemporal Integration of Optical Flow Vectors for Micro-expression DetectionProceedings of the 16th International Conference on Advanced Concepts for Intelligent Vision Systems - Volume 938610.1007/978-3-319-25903-1_32(369-380)Online publication date: 26-Oct-2015
  • (2014)A nonparametric approach to region-of-interest detection in wide-angle viewsPattern Recognition Letters10.1016/j.patrec.2014.05.01949:C(24-32)Online publication date: 1-Nov-2014
  • (2013)A survey of appearance models in visual object trackingACM Transactions on Intelligent Systems and Technology10.1145/2508037.25080394:4(1-48)Online publication date: 8-Oct-2013
  • (2012)The Gaussian mixture MCMC particle algorithm for dynamic cluster trackingAutomatica (Journal of IFAC)10.1016/j.automatica.2012.06.08648:10(2454-2467)Online publication date: 1-Oct-2012
  • (2011)Detection and tracking of multiple similar objects based on color-patternProceedings of the Second international conference on Autonomous and intelligent systems10.5555/2026956.2026986(273-283)Online publication date: 22-Jun-2011
  • Show More Cited By

View Options

View options

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media