Visual Sentiment Analysis: An Analysis of Emotions in Video and Audio

Deshmukh, Rushali A.; Amati, Vaishnavi; Bhamare, Anagha; Jadhav, Aditya

doi:10.1007/978-981-99-6586-1_21

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Using Vsa To Increase Personalization1

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2024

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“…VSA technology processes the video input by identifying facial expressions, body language and voice tones to determine the viewer's feelings in real time. This analysis provides a deep understanding of how content affects emotions, which can be used to personalize experiences in ways that resonate more deeply with each individual [13,14].…”

Section: Using Vsa To Increase Personalizationmentioning

confidence: 99%

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

Kuliahin

2024

CNCS

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Topicality. In connection with the development of AR technologies and their use in interactive art, there is a growing need to develop methods of personalizing visual content, focused on the individual preferences of users. Research methods. Neural collaborative filtering method, generalized matrix factorization method, mood analysis on video. The purpose of the article: Researching the possibilities of improving the personalization of visual content in interactive art by evaluating the emotional reactions of users and their implicit feedback. The results obtained. The application of neural collaborative filtering and generalized matrix factorization to create adapted visual content in interactive art in AR was considered, which will significantly increase the relevance and immersion of users in interactive works. Conclusion. The considered approach can be used to improve immersiveness and personalization during user interaction with interactive art in AR.

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Section: Using Vsa To Increase Personalizationmentioning

confidence: 99%

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

Kuliahin

2024

CNCS

View full text Add to dashboard Cite

show abstract

Visual Sentiment Analysis: An Analysis of Emotions in Video and Audio

Cited by 1 publication

References 15 publications

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

Personalization of Visual Content of Interactive Art in Augmented Reality Based on Individual User Preferences

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