A robust method for block-based motion estimation in RGB-image sequences

In this paper the block-based motion analysis in monocular RGB-image sequences is considered. The motion analysis is realized using a combined matching criterion, that represents a robust similarity measure for image blocks in successive images. This criterion is calculated as a weighted combination of the 3 color-specific matching criteria. The weight of each of these channel-specific criteria is determined based on their reliability. The combined criterion is used to measure translational and rotational motion between 2 successive images. Assuming these measuring values, a model based recursive estimation technique (Kalman filter) is applied to estimate the position and the velocity of the respective region. In order to cope with problematic image situations (e.g. partial occlusion) an extension of the conventional filter by a recognition system is proposed. This system recognizes typical distorted matching criteria and controls the adaptation of the filter