- Work feedback is essential in Job Environment to keep a report between Management and Workers. There are three main factors that contribute to a worker’s progress: behavioral, emotional, and cognitive.
- The major component of human communication is facial expressions and Speech Signals. Facial and Speech expressions are used not only to express our emotions but also to provide important communicative clues during social interaction, such as our level of interest, and continuous feedback signaling understanding of the information conveyed.
- The system automatically detects frontal faces in the video stream and codes each frame with respect to 7 dimensions: Neutral, anger, disgust, fear, joy, sadness, and surprise. The facial features from the video source is extracted and mapped with the basic emotions.
- This can be used in any kind of environment. Also, It can Analyze Speech Signals to Identify the Stress level of an Employee.
In the beginning, facial expression analysis was essentially a research topic for psychologists. However, recent progresses in image processing and pattern recognition have motivated significantly research works on automatic facial expression recognition. In the past, a lot of effort was dedicated to recognize facial expression in still images.
The automatic facial expression recognition system includes:
- Face Detector.
- Facial feature extractor for mouth, left and right eye. Facial Characteristic Point – FCP extractor.
- Facial expression recognizer
- In Existing system the major depression is one of the most frequent types of problem. There are almost nearly 450 million people suffering from depression.
- Some approaches use the temperature of the finger, human gestures and eye blink as a modality to detect stress.
- Recent techniques employ thermal imaging, physiological signals for stress detection
- Depression and Suicide is a multifaceted problem.
- Identification of Risk factor is difficult.
- Less functionality
- The main objective of this project is to design an efficient and accurate algorithm that would detect behavior analysis of the worker, behavior detection of the worker.
- It saves the man power and time of the faculty.
- For the face detection to work efficiently, we need to provide an input image which should not be blur or printed. We have used algorithm that is used for face detection and facial feature extraction.
- Also this system can recognize the Speech signals of the person with Feature Extraction Can be Done via MFCC feature Extraction from that it can analyze the stress level of the person using Speech Signals also..
- Front End – Anaconda IDE
- Backend – SQL
- Language – Python 3.8
- •Hard Disk: Greater than 500 GB
- •RAM: Greater than 4 GB
- •Processor: I3 and Above
- * Base Paper
- * Complete Source Code
- * Complete Documentation
- * Complete Presentation Slides
- * Flow Diagram
- * Database File
- * Screenshots
- * Execution Procedure
- * Readme File
- * Addons
- * Video Tutorials
- * Supporting Softwares
- * 24/7 Support * Ticketing System
- * Voice Conference
- * Video On Demand
- * Remote Connectivity
- * Code Customization
- * Document Customization
- * Live Chat Support
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