Abstract: In this paper, a new method was presented for spatiotemporal segmentation of moving-object using boundary evaluation in infrared video. At first, the ideal seeds of every moving object were extracted based on the holes effect of temporal difference, respectively. The wok focus was spatial segmentation. On the basis of the relationship between the global and local standard deviation of seeds, the segmented masks could be grown form the ideal seeds by using different growing thresholds. For determination of the best growing threshold, a criterion was constructed for evaluating the boundary of the segmented mask of infrared moving-object without prior knowledge. According to the proposed criterion, an iterative model which was segmentation-evaluation-segmentation-evaluation and the search method called as coarse to fine were applied to find the best growing threshold. Meanwhile the best segmented mask was obtained too. The experiment results show that the proposed method is superior and effective on segmentation of moving object in infrared video.