Real Time Driver Fatigue Detection SystemBased on Multi-Task ConNN

Real Time Driver Fatigue Detection SystemBased on Multi-Task ConNN

₹5,500.00
Product Code: python, Deep Learning
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Product Description

Aim:

          This paper aim to detect Real time driver's fatigue state using Convolutional Neural Network (CNN)


Synopsis:

            Drowsy driving is one of the major causes of road accidents and death. Hence, detection of driver’s fatigue and its indication is an active research area. Most of the conventional methods are either vehicle based, or behavioral based or physiological based. Few methods are intrusive and distract the driver, some require expensive sensors and data handling. Therefore, in Existing study, a low cost, real time driver’s drowsiness detection system is developed with acceptable accuracy. Facial landmarks on the detected face are pointed and subsequently the eye aspect ratio and mouth opening ratio are computed and depending on their values, drowsiness is detected based on developed adaptive thresholding.

            In the proposed system, a webcam records the video and driver’s face is detected in each frame employing image processing techniques. A novel system for evaluating the driver’s level of fatigue based on face tracking and facial key point detection. In order to track the driver’s face using CNN (Convolution Neural Network) and then the facial regions of detection based on facial key points. Then the eyes and mouth will be detected if the eye is closed the alert system will be displayed.


Proposed System  


             In the proposed system, a webcam records the video and driver’s face is detected in each frame employing image processing techniques. A novel system for evaluating the driver’s level of fatigue based on face tracking and facial key point detection. In order to track the driver’s face using CNN (Convolution Neural Network) and then the facial regions of detection based on facial key points. Then the eyes and mouth will be detected if the eye is closed the alert system will be displayed.




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  2. Abstract
  3. Base paper
  4. Full Project PPT
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  7. Source Code
  8. Screen Shots & Photos
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  10. Reference Papers
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The Delivery time for Hardware projects is 7-8 working days.

   

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  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

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  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.