_:n6921723ffdd64b259fcfb202929b506axb71
<http://schema.org/description>
"Video contents have become a critical tool for promoting products in\nE-commerce. However, the lack of automatic promotional video generation\nsolutions makes large-scale video-based promotion campaigns infeasible. The\nfirst step of automatically producing promotional videos is to generate visual\nstorylines, which is to select the building block footage and place them in an\nappropriate order. This task is related to the subjective viewing experience.\nIt is hitherto performed by human experts and thus, hard to scale. To address\nthis problem, we propose WundtBackpack, an algorithmic approach to generate\nstorylines based on available visual materials, which can be video clips or\nimages. It consists of two main parts, 1) the Learnable Wundt Curve to evaluate\nthe perceived persuasiveness based on the stimulus intensity of a sequence of\nvisual materials, which only requires a small volume of data to train; and 2) a\nclustering-based backpacking algorithm to generate persuasive sequences of\nvisual materials while considering video length constraints. In this way, the\nproposed approach provides a dynamic structure to empower artificial\nintelligence (AI) to organize video footage in order to construct a sequence of\nvisual stimuli with persuasive power. Extensive real-world experiments show\nthat our approach achieves close to 10\nby human testers, and 12.5\nperforming state-of-the-art approach."
<https://deepai.org/profile/lizhen-cui>