Video advertising is one of the most effective forms of advertisements because videos are more attractive, more persuasive, and more informative than images or texts. Increasing amounts of video advertisements requires faster and more intelligent technologies for video generation. We have developed a multi-modal video editing approach that can automatically generate advertising video clips from any source videos. We conduct chronological boundary segmentation of the original video and construct a weighted directed graph to assemble different segments. Experiments on our video editing datasets validate success of the proposed method in producing compelling and consistent advertising videos.

In the copper electrolytic refining process, the short-circuit failure among the electrodes usually exists. When it occurs, the temperature distribution is often abnormal, accompanied by local or overall overheating. This paper proposes a novel processing method for infrared temperature images to effectively detect the short-circuit fault and locate the accurate malfunctioning spots. The design procedure contains contrast enhancement, filter denoising, edge detection, image segmentation, high temperature electrode positioning. Finally, experimental results show that the proposed method can guarantee real-time processing of the infrared image of the electrolytic cell and accurately mark the malfunctioning position of electrodes with high temperature fault.