Implementation and Analysis of Sentimental Analysis on Facial Expression Using HAAR Cascade Methods

The sentimental analysis is phenomenon of exploring, analyzing and organizing human feelings. It is a process of extracting feelings of human faro pictures. It involves the separation of image into various characters such as face, background, etc. It uses lips and eye shape for extracting human feelings. It uses numerous of applications such as Pycharm Numpy ,Open CV, Python,etc. Its main objective is to find out the moods of human such as happy , sad ,etc. This report generates the emotional state of human being as well as different emotion of human in different situation.

[1]  Manpreet Kaur,et al.  ROI Based Medical Image Compression for Telemedicine Application , 2015 .

[2]  Xun Wang,et al.  A New Facial Expression Recognition Method Based on Geometric Alignment and LBP Features , 2014, 2014 IEEE 17th International Conference on Computational Science and Engineering.

[3]  Qiang Liu,et al.  Task modulations of racial bias in neural responses to others' suffering , 2014, NeuroImage.

[4]  Jianhua Zhang,et al.  Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review , 2020, Inf. Fusion.

[5]  G. Marijnissen,et al.  Different brain responses during empathy in autism spectrum disorders versus conduct disorder and callous-unemotional traits. , 2016, Journal of child psychology and psychiatry, and allied disciplines.

[6]  S. Dayan,et al.  Complications of botulinum toxin A use in facial rejuvenation. , 2003, Facial plastic surgery clinics of North America.

[7]  P. Johnston,et al.  Facial Emotion Modulates the Neural Mechanisms Responsible for Short Interval Time Perception , 2013, Brain Topography.

[8]  Z. Dienes,et al.  Whether others were treated equally affects neural responses to unfairness in the Ultimatum Game. , 2015, Social cognitive and affective neuroscience.

[9]  Hirotaka Osawa,et al.  Investigation of the effects of nonverbal information on werewolf , 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[10]  Gholamreza Anbarjafari,et al.  Emotion Recognition from Skeletal Movements , 2019, Entropy.

[11]  K. Kohara,et al.  Perceived age of facial features is a significant diagnosis criterion for age‐related carotid atherosclerosis in Japanese subjects: J‐SHIPP study , 2012, Geriatrics & gerontology international.

[12]  Manjit Kaur,et al.  An efficient image encryption using non-dominated sorting genetic algorithm-III based 4-D chaotic maps , 2019, Journal of Ambient Intelligence and Humanized Computing.

[13]  Riitta Hari,et al.  The compassionate brain: humans detect intensity of pain from another's face. , 2006, Cerebral cortex.

[14]  Sunil Agrawal,et al.  Image denoising review: From classical to state-of-the-art approaches , 2020, Inf. Fusion.

[15]  M. Balconi,et al.  Empathy, Approach Attitude, and rTMs on Left DLPFC Affect Emotional Face Recognition and Facial Feedback (EMG) , 2016 .

[16]  G. Rizzolatti,et al.  Pathways for smiling, disgust and fear recognition in blindsight patients , 2017, Neuropsychologia.

[17]  B. Starnes,et al.  Functional and survival outcomes in traumatic blunt thoracic aortic injuries: An analysis of the National Trauma Databank. , 2009, Journal of vascular surgery.

[18]  Kshitij Sharma,et al.  Building pipelines for educational data using AI and multimodal analytics: A "grey-box" approach , 2019, Br. J. Educ. Technol..

[19]  Manjit Kaur,et al.  Multi-objective differential evolution based random forest for e-health applications , 2019, Modern Physics Letters B.

[20]  Wojciech Zajkowski,et al.  A neural model of mechanisms of empathy deficits in narcissism , 2013, Medical science monitor : international medical journal of experimental and clinical research.