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Real Time Multiple Face detection from Live Camera, a Step towards Automatic Attendance System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 45 - Number 4 |
| Year of Publication: 2012 |
| Authors: Raikoti Sharanabasappa, Sanjaypande M. B |
10.5120/6771-9057
|
Raikoti Sharanabasappa, Sanjaypande M. B . Real Time Multiple Face detection from Live Camera, a Step towards Automatic Attendance System. International Journal of Computer Applications. 45, 4 ( May 2012), 45-49. DOI=10.5120/6771-9057
Abstract
Student attendance system is manual in most part of the world with essential Roll call and answering taking significant time. The objective of this work is to propose a model in openCV that captures live stream from camera and enables multiple face detection and segmentation. The segmented faces can further be used to recognize the students. As such the system leads towards the development of automatic attendance system, where the camera can be static and periodically can take the snap of the class. Further each image is processed to extract the faces. Haar cascade is used for face detection and Gaussian mixture model is used for face segmentation. A test over 1000 images reveals a result with 83% accuracy where accuracy is measured in terms of number of actual face detected v/s the number of faces present in a scene. The test are generated in various angles and light intensity.
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