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      Understanding cartoon emotion using integrated deep neural network on large dataset

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          Abstract

          Emotion is an instinctive or intuitive feeling as distinguished from reasoning or knowledge. It varies over time, since it is a natural instinctive state of mind deriving from one’s circumstances, mood, or relationships with others. Since emotions vary over time, it is important to understand and analyze them appropriately. Existing works have mostly focused well on recognizing basic emotions from human faces. However, the emotion recognition from cartoon images has not been extensively covered. Therefore, in this paper, we present an integrated Deep Neural Network (DNN) approach that deals with recognizing emotions from cartoon images. Since state-of-works do not have large amount of data, we collected a dataset of size 8 K from two cartoon characters: ‘Tom’ & ‘Jerry’ with four different emotions, namely happy, sad, angry, and surprise. The proposed integrated DNN approach, trained on a large dataset consisting of animations for both the characters ( Tom and Jerry), correctly identifies the character, segments their face masks, and recognizes the consequent emotions with an accuracy score of 0.96. The approach utilizes Mask R-CNN for character detection and state-of-the-art deep learning models, namely ResNet-50, MobileNetV2, InceptionV3, and VGG 16 for emotion classification. In our study, to classify emotions, VGG 16 outperforms others with an accuracy of 96% and F1 score of 0.85. The proposed integrated DNN outperforms the state-of-the-art approaches.

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          Most cited references28

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          Emotion recognition in human-computer interaction

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            • Article: not found

            Facial Expressions of Emotion

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              • Record: found
              • Abstract: not found
              • Article: not found

              Automatic analysis of facial expressions: the state of the art

                Bookmark

                Author and article information

                Contributors
                nikita.jain@bharatividyapeeth.edu
                vedika.gupta@bharatividyapeeth.edu
                shbhm3199@gmail.com
                madanagam@gmail.com
                ankitchaudhary3010@gmail.com
                santosh.kc@usd.edu
                Journal
                Neural Comput Appl
                Neural Comput Appl
                Neural Computing & Applications
                Springer London (London )
                0941-0643
                1433-3058
                21 April 2021
                : 1-21
                Affiliations
                [1 ]GRID grid.411685.f, ISNI 0000 0004 0498 1133, Department of Computer Science and Engineering, , Bharati Vidyapeeth’s College of Engineering, ; Dehi, India
                [2 ]GRID grid.267169.d, ISNI 0000 0001 2293 1795, KC’s PAMI Research Lab - Computer Science, , University of South Dakota, ; 414 E Clark St, Vermillion, SD 57069 USA
                Article
                6003
                10.1007/s00521-021-06003-9
                8059693
                44b78878-0b1f-40d8-b17b-b7b174745e30
                © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                Categories
                S.i. : Ncacvip

                Neural & Evolutionary computing
                animation,cartoon,character detection,convolutional neural network,emotion,face segmentation,mask r-cnn,vgg16

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