Citation

Nagappan, Sidharrth and Tan, Jia Qi and Wong, Lai Kuan and See, John Su Yang (2023) Context-Aware Multi-Stream Networks for Dimensional Emotion Prediction in Images. In: 2023 IEEE International Conference on Image Processing (ICIP), 08-11 October 2023, Kuala Lumpur, Malaysia.

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Abstract

Teaching machines to comprehend the nuances of emotion from photographs is a particularly challenging task. Emotion perception— naturally a subjective problem, is often simplified for computational purposes into categorical states or valence-arousal dimensional space, the latter being a lesserexplored problem in the literature. This paper proposes a multi-stream context-aware neural network model for dimensional emotion prediction in images. Models were trained using a set of object and scene data along with deep features for valence, arousal, and dominance estimation. Experimental evaluation on a large-scale image emotion dataset demonstrates the viability of our proposed approach. Our analysis postulates that the understanding of the depicted object in an image is vital for successful predictions whilst relying on scene information can lead to somewhat confounding effects.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	dimensional emotion, image emotion prediction, emotional analysis, deep neural networks, DES.
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	23 Feb 2024 03:52
Last Modified:	23 Feb 2024 03:52
URII:	http://shdl.mmu.edu.my/id/eprint/12128

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