A method has been developed to identify video shots of the same scene where camera flash lights are observed, and the method has been tested by using it to detect such shots from a large TV video archive. Camera flashes are often used in impressive scenes, such as interviews of important persons. Because such scenes are broadcasted repeatedly on various TV programs, a method for detecting them is a promising approach for semantic video indexing. The proposed identification method is invariant to the differences in viewpoint, illumination or any other visual environment because it depends on comparison between temporal occurrence patterns of flash lights. Furthermore, because each flash pattern is represented with a binary array, the comparison requires low computing cost. These advantages mean that the proposed method can be considered to provide semantic and efficient video analysis.