Scene-driven Retrieval in Edited Videos using Aesthetic and Semantic Deep Features

Lorenzo Baraldi, Costantino Grana, Rita Cucchiara
2016 Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval - ICMR '16  
This paper presents a novel retrieval pipeline for video collections, which aims to retrieve the most significant parts of an edited video for a given query, and represent them with thumbnails which are at the same time semantically meaningful and aesthetically remarkable. Videos are first segmented into coherent and story-telling scenes, then a retrieval algorithm based on deep learning is proposed to retrieve the most significant scenes for a textual query. A ranking strategy based on deep
more » ... tures is finally used to tackle the problem of visualizing the best thumbnail. Qualitative and quantitative experiments are conducted on a collection of edited videos to demonstrate the effectiveness of our approach.
doi:10.1145/2911996.2912012 dblp:conf/mir/BaraldiGC16 fatcat:24rn5dlkkfgolmbq5lisva2ski