A Novel Framework for Estimating Viewer Interest by Unsupervised Multimodal Anomaly Detection

A reliable method to estimate viewer interest is highly sought after for human-centered video information retrieval. A method that estimates viewer interest while users are watching Web videos is presented in this paper. The method uses a framework for anomaly detection based on collaborative use of...

Full description

Bibliographic Details
Main Authors: Yuma Sasaka, Takahiro Ogawa, Miki Haseyama
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8289336/