Color clustering for scene change detection and object tracking in video sequences

摘要

Pixel data (P) forming an image (12) is clustered into groups of data of similar color. Pixels of approximately the same color form one cluster (16). A vigilance parameter determines how many clusters (16) are derived and how wide a range of colors are included in a cluster. The process for allocating input vectors into clusters is based upon a minimum distance measure to multiple prototype vectors. A given image frame is allocated into clusters in an iterative process. A subset of clusters from an initial image frame are treated as featured clusters. The featured clusters correspond object(s). To track the object, input vectors in subsequent frames are tested to determine whether they correspond to a featured cluster. A scene change is detected when more than a prescribed number of prototype vectors have changed by more than a predetermined amount.