Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-35725-1_10
Title: Interactive video advertising: A multimodal affective approach
Authors: Yadati, K.
Katti, H. 
Kankanhalli, M. 
Issue Date: 2013
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)
URI: http://scholarbank.nus.edu.sg/handle/10635/78200
ISBN: 9783642357244
ISSN: 03029743
DOI: 10.1007/978-3-642-35725-1_10
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