HOTFLASHES: THUMBNAILING VIDEOS OF SOCIAL GATHERINGS BY DETECTING CAMERA FLASH ILLUMINATED FRAMES
Shiva Sundaram, Vladan Velisavljevic, Yujie QinAbstract
Automatic annotation of video clips is desired to efficiently thumbnail user generated content available in the Internet. Automatic techniques typically focus on a selected set of inherent video features (such as scene-cut or shot boundaries) that are deemed to be salient. Along this line, the presence of camera flash light illumination is a feature of interest. This event is usually triggered manually (by a photographer) within a scene and the selected frame(s) they occur in are deemed to be interesting in the recording: for instance, the appearance of a celebrity in a party. In this paper we present a method to detect video frames that contain flashes originating from still cameras in user generated video clips. We focus on designing features for flash illumination detection using various measures of luminance change within video sequences. Using the proposed method, we obtain detection performance of approximately 89% which is 8% absolute improvement over the baseline method that uses only change in average illumination. We also illustrate a case where flashes are automatically detected in video clips of social gatherings that can be used for thumbnailing and browsing.
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