A change detection method for image sequences based on physical models

Change detection methods are used to detect changes between two frames in an image sequence. Fundamental techniques for detecting changes use a difference image between the two frames. The change of each pixel is detected if difference values exceed a pre-set threshold, which is determined on the basis of the estimated value of the variance of noises on the frames. Not only the noises on the frames but also illumination changes between the frames are critical problems for change detection. A recently proposed approach gives a threshold derived from the average of the difference image over areas which are estimated as non-change parts. However, such a threshold may not be appropriate since the approach uses no physical parameters such as light sources, the reflection of objects. This paper proposes a new change detection method based on a physical model, which describes physical parameters such as light sources and the reflection of objects, known as an illumination model. First, we show the derivation of a new threshold based on the illumination model. The threshold is derived from the angle of the light of sources, the gray level of background objects, and the normal-vector of the background objects. A new change detection algorithm using such a threshold is shown. Next, we show experimental results and comparison, in which the proposed method improves the accuracy of detection results, compared to change detection by using the conventional threshold. We also give discussion on the features of the proposed method.