Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation

Authors:
R. Feghali;A. Mitiche
Affiliations:
INRS-EMT, Montreal, Que., Canada;-
Venue:
IEEE Transactions on Image Processing
Year:
2004

Citing 0
Cited 4

Parametric active contours for object tracking based on matching degree image of object contour points

Pattern Recognition Letters
Video segmentation based on motion coherence of particles in a video sequence

IEEE Transactions on Image Processing
Integrating the projective transform with particle filtering for visual tracking

Journal on Image and Video Processing - Special issue on advanced video-based surveillance
3D Video Based Segmentation and Motion Estimation with Active Surface Evolution

Journal of Signal Processing Systems

Quantified Score

Hi-index	0.01

Visualization

Abstract

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image sequence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine simultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion boundary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.