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@article{170726,
        author = {Mr. Rohan Patil and Dr.  Bashirahamad Momin},
        title = {A Review on Human Behavior Analytics in Surveillance System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {1632-1644},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170726},
        abstract = {Facial Emotion Recognition (FER) has become a crucial topic of study in domains including security, healthcare, and human-computer interaction. A thorough analysis of the most recent techniques, models, and datasets utilized in FER is provided in this review study. Existing surveys were analyzed to identify research gaps and address areas needing improvement. FER datasets are categorized into six emotions sadness, happi- ness, fear, anger, surprise and disgust. The key steps of FER pre-processing, feature extraction and classification are covered in this paper along with a comparison of several deep learning- based models and their performance standards. Challenges such as dataset imbalance, real-time processing, cultural biases, and model scalability are highlighted, along with potential solutions. Additionally, future trends like multi-modal approaches, transfer learning, and reinforcement learning for personalized emotion detection are explored. The findings offer insights into model selection for specific datasets and applications, helping future researchers develop robust face emotion recognition systems. This review aims to facilitate advancements in FER by guiding the creation of scalable and adaptable models capable of performing effectively in real-world surveillance and other applications.},
        keywords = {Facial Emotion Recognition (FER), Deep Learn- ing, Human-Computer Interaction, Transfer Learning, Surveil- lance Systems.},
        month = {December},
        }