Facial parts detection using Viola Jones algorithm

Vikram, K.; Padmavathi, S

doi:10.1109/icaccs.2017.8014636

Cited by 93 publications

(52 citation statements)

References 7 publications

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“…Therefore for optimize the GPUs performance and reduce the training time The Image Net database consists of 15millions high-resolution images with 22 thousand lab image classes. Alexnet [21][22] is one of the pre trained CNN models used to classify objects. used images for training from either Image Places365 datasets.…”

Section: Convolution Neural Networkmentioning

confidence: 99%

Facial Spots Detection Using Convolution Neural Network

Bose

Bandyopadhyay

2020

AJRCoS

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Nowadays security became a major global issue. To manage the security issue and its risk, different kinds of biometric authentication are available. Face recognition is one of the most significant processes in this system. Since the face is the most important part of the body so the face recognition system is the most important in the biometric authentication. Sometimes a human face affected due to different kinds of skin problems, such as mole, scars, freckles, etc. Sometimes some parts of the face are missing due to some injuries. In this paper, the main aim is to detect a facial spots present in the face. The total work divided into three parts first, face and facial components are detected. The validation of checking facial parts is detected using the Convolution Neural Network (CNN). The second part is to find out the spot on the face based on Normalized Cross-Correlation and the third part is to check the kind of spot based on CNN. This process can detect a face under different lighting conditions very efficiently. In cosmetology, this work helps to detect the spots on the human face and its type which is very helpful in different surgical processes on the face.

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Section: Convolution Neural Networkmentioning

confidence: 99%

Facial Spots Detection Using Convolution Neural Network

Bose

Bandyopadhyay

2020

AJRCoS

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“…The Viola-Jones face detection algorithm is the first framework based on object detection that provides good detection rates in realtime is given by Paul Viola & Michael Jones in the year of 2001. This algorithm has been implemented in a software 'Matlab' [7]. This algorithm basically consist of below mentioned algorithms.…”

Section: A Viola Jones Algorithmmentioning

confidence: 99%

Automatic Attendance System using Matlab

Saxena¹

2018

IJRASET

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In this paper we are proposing an automatic attendance system which can be used in every organization to mark the attendance of employees. The main application of Automatic attendance system is seen in teaching institutions, where the attendance of students has to be regularly monitored on daily basis. The method developed provides a secure and effective may recording attendance. Automatic attendance system uses mainly two algorithms i.e. Viola Jones Algorithm and Local binary pattern algorithm. Viola Jones algorithm is used for face detection and Local binary pattern is used for the feature extraction and face recognition.

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“…In the face detection stage, it uses the HAAR's algorithm and for recognition stage it uses the EIGEN values. The Research work in [3] presented a model that is composed of two-mode tracking: short range tracking mode, and long-range tracking mode. This model is used to deal with real-time face tracking situations, face scaling, face pose changes, and face abrupt movements.…”

Section: Releted Workmentioning

confidence: 99%

Automatic Facial Recognition and Surveillance System

Patel¹

2018

IJRASET

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In this paper we proposed a criminal detection framework that could help policemen to recognize the face of a criminal or a suspect. The framework is a client-server based face recognition surveillance in the real-time. For detecting human faces, we use Viola Jones algorithm which uses haar wavelet classifier and PCA (Principal component analysis). We train computer to automatically identify the human faces from the given images irrespective of the illumination conditions. There were some disadvantages like intensity of light problem and head pose problem. Therefore, to overcome these issues, various techniques like illumination invariant, Viola and Jones algorithm, Principle component analysis are used. The major steps in this system are detecting the faces and recognizing them. After these, the comparison of detected faces can be done by crosschecking with the database

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Facial parts detection using Viola Jones algorithm

Cited by 93 publications

References 7 publications

Facial Spots Detection Using Convolution Neural Network

Facial Spots Detection Using Convolution Neural Network

Automatic Attendance System using Matlab

Automatic Facial Recognition and Surveillance System

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