Please use this identifier to cite or link to this item:
|Title:||Interactive video advertising: A multimodal affective approach|
|Source:||Yadati, K.,Katti, H.,Kankanhalli, M. (2013). Interactive video advertising: A multimodal affective approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7732 LNCS (PART 1) : 106-117. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-35725-1_10|
|Abstract:||Online video advertising (video-in-video) strategies are typically agnostic to the video content (ex.: advertising on YouTube) and the human viewer's preferences. How to assess the emotional state and engagement of the viewer to place an advertisement? Where to insert an advertisement based on the content in an advertisement and a specific target video stream? Surely these are relevant questions that should be addressed by a good model for video advertisement placement. In this paper, we propose a novel framework to address two important aspects of (a) multi-modal affective analysis of video content and viewer behavior (b) a method for interactive personalized advertisement insertion for a single user. Our analysis and framework is backed by a systematic study of literature in marketing, consumer psychology and affective analysis of videos. Results from the user-study experiments demonstrate that the proposed method performs better than the state-of-the-art in video-in-video advertising. © Springer-Verlag 2013.|
|Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 21, 2018
checked on Feb 24, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.