|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 183 - Number 24
|Year of Publication: 2021
|Authors: D.A. Vidhate, Pallavi Kumatkar, Vaishali Zine, Vaishnavi Kalyankar, Rutuja Satpute, Shruti S. Pophale
D.A. Vidhate, Pallavi Kumatkar, Vaishali Zine, Vaishnavi Kalyankar, Rutuja Satpute, Shruti S. Pophale . Depression Scale Recognition Over Fusion of Visual and Vocal Expression using Artificial Intellectual Method. International Journal of Computer Applications. 183, 24 ( Sep 2021), 16-19. DOI=10.5120/ijca2021921607
In Automatic depression assessment supported visual and vocal cues may be a rapidly growing research domain. This exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image processing and machine learning algorithms. Visual indication of depression, many proceed used for data gathering, and existing datasets are reviewed. The article describes techniques and algorithms for visual feature extraction, dimensionality reduction, decision methods for classification, and regression approaches, also as different fusion strategies. A quantitative meta-analysis of reported results, counting on performance metrics robust to chance, is included, identifying general trends and key pending issues to be treated in future studies of automatic depression assessment utilizing visual and vocal cues alone or together with cues. The proposed work also administered to predict Depression levels consistent with the current input of videos using deep learning also as NLP.