Identification of a human using accorded blobs on the varied region from image sequence by multiple cameras

This paper proposes a method to identify the same person in different-view images using plane homography. We address the problem of correspondence under multiple uncalibrated cameras. For solving this problem, we propose a three steps process. The first, we detect intensity-varied regions in the each image sequence by background subtraction. The background model has the temporal-median value for each pixel and it updates by itself in the process. The temporal difference between consecutive images contributes to detect accurately in the result of background subtraction. The second step is generating the set of blobs from detected varied regions in the each image sequence. Those blobs are generated using criterion with specific color range. Each blob is described probability distribution with color and location information in the image plane. The final step is matching the current color blobs with other blobs in the different images using maximum likelihood estimation. The matched color blobs are reconstructed to the human silhouette by context information that includes restriction conditions on the human body. Finally we identify matched human in the different images without calibration.