This paper proposes a method of recognising Japanese sign language indirectly using a colored glove which has multiple color patches on its surface. Japanese sign language has finger alphabets and words which include a hand motion. In the proposed method, the finger alphabets are estimated from three parameters: the color combination of the visible patches, the dispersion of the visible patches, and the hand direction. The color combination is represented by the mean of the color histogram of the visible patches in an input image. Words which include a hand motion are estimated from the transition of characteristic hand structures which are detected from an image sequence by changes in the color combination of the visible patches. The experimental results show the validity of the proposed method.

We propose a qualitative analysis of group behaviour based on multi-scale region analysis. In the algorithm, histogram backprojection images of an input image sequence are analyzed with multi-scale filters to extract a hierarchical representation of the group structure in the sequence. The dynamics of the hierarchical description is interpreted from the temporal aspect of qualitative relations among groups. Occlusions are also detected with transition rules. A soccer game image sequence is chosen as an example of the analysis.>