Generalized ELL for detecting and tracking through illumination model changes

In previous work, we developed the Illum-PF-MT, which is the PFMT idea applied to the problem of tracking temporally and spatially varying illumination change. In many practical problems, the rate at which illumination changes varies over time. For e.g. when a car transitions from shadow to sunlight or vice-versa the rate of illumination change is much higher than when it is in shadow or in sunlight. One way to model illumination change in such problems is using a Gaussian random walk model with two values of the change covariance - a large covariance when a “transition” is detected and a much smaller one when “no transition” is detected. But to use such a model, one needs to rst detect the transition. The transition is a natural one and so it happens gradually (unlike a sudden manual dimming of the light in the room) and thus existing change detection statistics which are designed only for sudden changes are unable to detect the transition. In this paper, we propose to use the re...

• Type: Conference
• Year: 2008
• Where: ICIP
• Authors: Amit Kale, Namrata Vaswani
• Keywords: Change Covariance, ICIP 2008, Illumination Change, Image Processing, Random Walk Model