In content-based video analysis, shot boundary detection is a common first step to segment video data into fundamental units of shots, each composing consecutive frames filmed with a single camera act. Many methods have been proposed in the literature for detection of shot boundaries. In this paper, we propose a new and effective post-refinement method on the detected shot boundaries by performing sequential detection of abrupt change in two underlying distributions. Experimental results show that the proposed method can eliminate most false detections and also recover many missed detections from the original detected shot boundaries, attaining better detection performance.