Improving Video Segmentation Algorithms by Detection of and Adaption to Altered
Johan Lindström, Finn Lindgren, Ulla Holst and Kalle Åström
Centre for Mathematical Sciences
Lund Institute of Technology,
Changing illumination constitutes a serious challenge for video segmentation
algorithms, especially in outdoor scenes under cloudy conditions. Rapid
illumination changes, e.g. caused by varying cloud cover, often cause existing
segmentation algorithms to erroneously classify large parts of the
image as foreground.
Here a method that extends existing segmentation algorithms by detecting
illumination changes using a CUSUM detector and adjusting the background
model to conform with the new illumination is presented. The method is shown
to work for two segmentation algorithms, and it is indicated how the method
could be extended to other algorithms.