Regions merging based on robust statistical testing

This paper addresses the problem of finding moving objects present in an image sequence. More specifically, a method is proposed to merge regions based on a coherent motion criterion. A modified Kolmogorov-Smirnov test is proposed which exploits both the motion information present in the residual distribution and the motion information of the motion parameter space. Therefore, all the available motion information is used. Moreover, the proposed test is consistent with robust motion estimation. Using the modified Kolmogorov- Smirnov test, the graph of the relationships between the different regions is built. The graph also integrates spatial information as only adjacent regions are allowed to merge. Two graph clustering rules are proposed which enable us to robustly define the moving objects. The proposed method does not require any user input. Simulation results demonstrate the efficiency of the proposed method.

[1]  P. Anandan,et al.  Hierarchical Model-Based Motion Estimation , 1992, ECCV.

[2]  Murat Kunt,et al.  Object tracking based on temporal and spatial information , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[3]  Andrew Lippman,et al.  Spatio-temporal segmentation based on motion and static segmentation , 1995, Proceedings., International Conference on Image Processing.

[4]  Michal Irani,et al.  Detecting and Tracking Multiple Moving Objects Using Temporal Integration , 1992, ECCV.

[5]  Jean-Marc Odobez,et al.  Robust Multiresolution Estimation of Parametric Motion Models , 1995, J. Vis. Commun. Image Represent..

[6]  Edward H. Adelson,et al.  Spatio-temporal segmentation of video data , 1994, Electronic Imaging.

[7]  Peter J. Rousseeuw,et al.  Robust regression and outlier detection , 1987 .

[8]  Frederic Dufaux,et al.  Segmentation-Based Motion Estimation for Second Generation Video Coding Techniques , 1996 .

[9]  Narsingh Deo,et al.  Graph Theory with Applications to Engineering and Computer Science , 1975, Networks.

[10]  Anil K. Jain Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.