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Capsule endoscopy (CE) is a revolutionary technology that enables physicians to examine the whole digestive tract in human body in a minimally noninvasive manner. However, it is reported that the large amount of video data yielded in each examination produces a troublesome and time consuming task for a clinician and it takes about two hours on average to examine. To reduce such a heavy load for clinicians, automatic video analysis for CE video is desired. Since each CE video contains about 60,000 frames, it may be necessary to divide such a long video into small segments. In this paper, we investigate the possibility of applying motion analysis approaches for this purpose. Two typical motion analysis methods, adaptive root patch search block matching and Bayesian multi-scale differential optical flow, are taken into account to show their ability for CE video segmentation. Experimental results suggest that motion information may be useful for CE video segmentation.