Abstract
In recent years the explosive development and growth of video technology and multimedia have created a new challenge in the field of computer vision. The tremendous increase in multimedia exchange like video, audio, image, etc., through the internet and other social media has led the way to content analysis. Content analysis is a technique to interpret textual data, multimedia data, and communication artifacts. In this paper we have provided an overview of content analysis and the more profound interpretation of video content analysis in a different area is shown. Specifically, in this paper, we have focused more on affective content analysis, its methodology, trends, and challenges.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zhao S, Ding G, Chua T-S, Schuller BW, Keutzer K (2018) Affective image content analysis: a comprehensive survey. In: Proceedings of the twenty-seventh international joint conference on artificial intelligence (IJCAI-18)-2018
Zhang L, Han Lau AC, Tjondronegoro D, Chandran V (2014) A pilot study on affective classification of facial images for emerging news topics. In: IEEE 16th international workshop on multimedia signal processing (MMSP), Jakarta, Indonesia, 22–24 Sep 2014
Mittal N, Sharma D, Joshi ML (2018) Image sentiment analysis using deep learning. In: IEEE/WIC/ACM international conference on web intelligence (WI)
Garcia AH (2017) Perceived emotion from images through deep interaction neural networks. In: 2017 seventh international conference on affective computing and intelligent (ACII)
Bao S, Ma H, Li W (2014) ThuPIS: a new affective image system for psychological analysis. In: 2014 IEEE international symposium on bioelectronics and bioinformatics (IEEE ISBB 2014)
Li N, **a Y, **a Y (2015) Semi-Supervised emotional classification of color images by learning from cloud. In: 2015 international conference on affective computing and intelligent interaction (ACII)
Rao T, Xu M, Liu H, Wang J, Burnett I (2016) Multi-Scale blocks based image emotion classification using multiple instance learning IEEE
Dimitrova N, Zhang H-J, Shahraray B, Sezan I, Huang T, Zakhor A (2002) Applications of video-content analysis and retrieval. IEEE
Shih H-C (2017) A survey on content-aware video analysis for sports IEEE Trans Circuits Syst Video Technol 99(9), Jan
Guan Y-P, Li JJ, Ye Y, Si J, Zhang H (2011) Content based sports video sequence analysis and synthesis-IEEE
Liu H-Y, Zhang H (2005) A sports video browsing and retrieval system based on multimodal analysis: Sportsbr. In: Proceedings of the fourth international conference on machine learning and cybernetics, Guangzhou, 18–21 Aug 2005
Russo MA, Kurniang goro L, Jo K-H (2019) Classification of sports videos with combination of deep learning models and transfer learning. In: 2019 international conference on electrical, computer and communication engineering (ECCE), 7–9 Feb 2019
Russo MA, Filonenko A, Jo K-H (2017) Sports classification in sequential frames using CNN and RNN, IEEE
Ashwin TS, Saran S, Mohana Reddy GR (2016) Video affective content analysis based on multimodalfeatures using a novel hybrid SVM-RBM classifier. In: 2016 IEEE Uttar Pradesh section international conference on electrical, computer and electronics engineering (UPCON), Indian Institute of Technology (Banaras Hindu University) Varanasi, India, 9–11 Dec 2016
Hanjalic A, Xu L-Q (2001) User-oriented affective video content analysis. IEEE
Hanjalic A (2003) Multimodal approach to measuring excitement in video. In: ICME, IEEE
Kang H-B (2003) Emotional event detection using relevance feedback. IEEE
Zheng Y, Zhu G, Jiang S, Huang Q, Gao W (2008) Visual-aural attention modeling for talk show video highlight detection. ICASSP, IEEE
Furini M (2015) ViMood: using social emotions to improve video indexing. In: 2015 12th annual ieee consumer communications and networking conference (CCNC)
Hanjalic A, Xu L-Q (2005) Affective video content representation and modeling. IEEE Trans Multimed 7(1), Feb
Zhu Y, Wang S, Ji Q (2015) Emotion recognition from users’ eeg signals with the help of stimulus videos. IEEE
Shahnaz C, Shoaib-Bin-Masud, Shafiul Hasan SM (2016) Emotion recognition based on wavelet analysis of empirical mode decomposed EEG signals responsive to music videos. In: 2016 IEEE region 10 conference (TENCON)—Proceedings of the international conference
Wang M-L, Lin C-W, Mayer NM, Hu M-H, Lee P-Y. An brain-computer interface for video content analysis system for perceive emotions by using EEG. In: 2016 international conference on consumer electronics-Taiwan
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Nayak, A.A., Dharmanna, L. (2021). A Comprehensive Survey on Content Analysis and Its Challenges. In: Suma, V., Bouhmala, N., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 53. Springer, Singapore. https://doi.org/10.1007/978-981-15-5258-8_70
Download citation
DOI: https://doi.org/10.1007/978-981-15-5258-8_70
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5257-1
Online ISBN: 978-981-15-5258-8
eBook Packages: EngineeringEngineering (R0)