Detection of Smart Selfie using Deep Learning
Objective
In this study we are implementing the application of smart selfie of a person using the open CV library
Abstract
We will employ computer vision in this study to perform real-time face detection and lip position tracking from high-definition video. Face detection and recognition are examples of a prominent topic in biometrics research is an image or a video. It has gotten a lot of attention because of its huge application value and market potential, such as real-time video surveillance system. For facial recognition and location tracking The OpenCV library is used to generate the lips. The results of the experiments were generated using computer vision and OpenCV. face detection framework libraries at 30 frames per second at 1080p resolutions for greater accuracy and speed monitoring the location of the lips and capturing a high-definition video intelligent selfie.
Keywords: Face detection, Smart selfie, Face recognition, Open CV, Dlib, Deep learning.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
H/W Specifications:
- Processor:
I5/Intel Processor
- RAM: 8GB (min)
- Hard Disk : 128 GB
S/W Specifications:
- Operating System: Windows 10
- Server-side Script: Python 3.6
- IDE: PyCharm,Jupyter notebook
- Libraries Used: Numpy, IO, OS, Flask, keras, pandas, tensorflow
Learning Outcomes
· Practical exposure to
· Hardware and software tools
· Solution providing for real time problems
· Working with team/individual
· Work on creative ideas
· Testing techniques
· Error correction mechanisms
· What type of technology versions is used?
· Working of Tensor Flow
· Implementation of Deep Learning techniques
· Working of CNN algorithm
· Working of Transfer Learning methods
· Building of model creations
· Scope of project
· Applications of the project
· About Python language
· About Deep Learning Frameworks
· Use of Data Science
Related Projects
Paper Publishing
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