TY - GEN
T1 - Emotion based image musicalization
AU - Zhao, Sicheng
AU - Yao, Hongxun
AU - Wang, Fanglin
AU - Jiang, Xiaolei
AU - Zhang, Wei
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/3
Y1 - 2014/9/3
N2 - Playing appropriate music when watching images can make the images vivid and bring people into their intrinsic world. In this paper, we propose to musicalize images based on their emotions. Most of previous works on image emotion analysis mainly used elements-of-art based low-level visual features, which are vulnerable to the arrangements of elements. Here we propose to extract visual features, inspired by the concept of principles-of-art, to recognize image emotions. To enrich the descriptive power, a dimensional perspective is introduced to emotion modeling. Experiments on the IAPS dataset demonstrate the superiority of the proposed method in comparison to the state-of-the-art methods for emotion regression. The music in MST dataset with approximate emotions to the recognized image emotions is selected to musicalize these images. The user study results show its effectiveness and popularity of the image musicalization method.
AB - Playing appropriate music when watching images can make the images vivid and bring people into their intrinsic world. In this paper, we propose to musicalize images based on their emotions. Most of previous works on image emotion analysis mainly used elements-of-art based low-level visual features, which are vulnerable to the arrangements of elements. Here we propose to extract visual features, inspired by the concept of principles-of-art, to recognize image emotions. To enrich the descriptive power, a dimensional perspective is introduced to emotion modeling. Experiments on the IAPS dataset demonstrate the superiority of the proposed method in comparison to the state-of-the-art methods for emotion regression. The music in MST dataset with approximate emotions to the recognized image emotions is selected to musicalize these images. The user study results show its effectiveness and popularity of the image musicalization method.
KW - Emotion recognition
KW - dimensional model
KW - elements and principles of art
KW - image musicalization
UR - https://www.scopus.com/pages/publications/84937126800
U2 - 10.1109/ICMEW.2014.6890565
DO - 10.1109/ICMEW.2014.6890565
M3 - 会议稿件
AN - SCOPUS:84937126800
T3 - 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
BT - 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
Y2 - 14 July 2014 through 18 July 2014
ER -