Improving object segmentation by reflection detection and removal

For object analysis in videos such as in video surveillance systems, the preliminary segmentation step is very important. Many segmentation methods using static camera have been proposed in the last decade, but they all suffer in occurrance of object reflection especially on the ground, i.e. reflected regions are also segmented as foregrounds. We present a new method which detects the border between the real object and its reflection. Experiments show that an outstanding improvement of segmentation results are obtained by removing the reflection part of the over-segmented objects.

[1]  F. E. Nicodemus,et al.  Geometrical considerations and nomenclature for reflectance , 1977 .

[2]  Touradj Ebrahimi,et al.  Accurate video object segmentation through change detection , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[3]  Larry S. Davis,et al.  A Robust Background Subtraction and Shadow Detection , 1999 .

[4]  Ramakant Nevatia,et al.  Tracking multiple humans in complex situations , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Peter Shirley,et al.  An Anisotropic Phong Light Reflection Model , 2000 .

[6]  Thomas Sikora,et al.  Comparison of static background segmentation methods , 2005, Visual Communications and Image Processing.

[7]  R. Love Surface reflection model estimation from naturally illuminated image sequences , 1997 .

[8]  Takeo Kanade,et al.  Surface Reflection: Physical and Geometrical Perspectives , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Qi Tian,et al.  Foreground object detection from videos containing complex background , 2003, MULTIMEDIA '03.

[10]  Jun Shen,et al.  Motion detection in color image sequence and shadow elimination , 2004, IS&T/SPIE Electronic Imaging.

[11]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).