Affective computing
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual information retrieval
Principles of visual information retrieval
Principles of visual information retrieval
Affect computing in film through sound energy dynamics
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Analysis of scene context related with emotional events
Proceedings of the tenth ACM international conference on Multimedia
Constructing table-of-content for videos
Multimedia Systems - Special section on video libraries
Video Scene Segmentation via Continuous Video Coherence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Affective content detection using HMMs
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Improved Perceptual Tempo Detection of Music
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Scene Determination Based on Video and Audio Features
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Systematic evaluation of logical story unit segmentation
IEEE Transactions on Multimedia
Affective video content representation and modeling
IEEE Transactions on Multimedia
Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
Personalized MTV Affective Analysis Using User Profile
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Utilizing affective analysis for efficient movie browsing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive local hyperplanes for MTV affective analysis
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Personalization in multimedia retrieval: A survey
Multimedia Tools and Applications
Multimedia Tools and Applications
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Extracting video structures is important for video indexing and navigation in large digital video archives. It is usually achieved by video segmentation algorithms. Little research efforts has been invested on segmentation solutions that utilize the video's emotional content. These solutions not only have the potential of providing better performances than existing segmentation methods, but are also able to provide a more natural video segmentation with which viewers can associate with. The development of an affect-based segmentation solution faces many challenges, such as the dynamic and time evolving nature of a video's emotional content. This paper introduces a novel computation method for affect-based video segmentation. It is designed based on the Pleasure-Arousal-Dominance (P-A-D) emotion model[18], which in principle can represent a large number of emotions. This method consists of a P-A-D estimation stage and a segmentation stage. A P-A-D estimator based on the Dynamic Bayesian Networks (DBNs) is proposed for the first stage. A clustering-based algorithm that utilizes the video's P-A-D information is proposed for the second stage. Experimental results demonstrate the feasibility of the method.