Face detection and geometric face normalization

Talele, Kiran; Kadam, S. A.

doi:10.1109/tencon.2009.5395980

Cited by 14 publications

(9 citation statements)

References 6 publications

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“…Ada boosting or Adaptive boosting is a machine learn ing algorith m is used to increase the performance level of a simp le learning algorith m. This is use for classification purpose [4]. It adds many weak classifiers to become a strong classifier.…”

Section: A Viola-jones Object Detection Frameworkmentioning

confidence: 99%

Comparative Survey of Face Recognition Techniques

2015

IJAERD

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Abstract-Face recognition has been a fast emergent and exciting area in real time applications. Automatic face recognition has shown great achievement for high-quality images under embarrassed conditions. In this paper techniques of Face detection along with Face Recognition are discussed. Human and object frames, background frames are separated by implementing a face detection algorithms like Viola-Jones & Skin Detection algorithms. In this paper we have discussed, analysed, & compare some popular face detection methods like PCA, LDA, PCA + LDA Hybridization and Gabor wavelet transformations and also tried to attempt a comparative study of these methods.

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Section: A Viola-jones Object Detection Frameworkmentioning

confidence: 99%

Comparative Survey of Face Recognition Techniques

2015

IJAERD

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“…In the process of sieving related literature (Talele and Kadam, 2009) or (Zakaria and Suandi, 2011), the Viola-Jones algorithm as well as an extended version of Eigenfaces enhanced through neural networks turned out to be the most feasible methods. A new revolution in Face Detection is introduced by Facebook called 'DeepFace' (Taigman et al, 2014).…”

Section: Face Detectionmentioning

confidence: 99%

Challenges and Limitations Concerning Automatic Child Pornography Classification

Moser¹,

Rybnicek

Haslinger

2015

Proceedings of the 10th International Conference on Computer Vision Theory and Applications

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The huge volume of data to be analyzed in the course of child pornography investigations puts special demands on tools and methods for automated classification, often used by law enforcement and prosecution. The need for a clear distinction between pornographic material and inoffensive pictures with a large amount of skin, like people wearing bikinis or underwear, causes problems. Manual evaluation carried out by humans tends to be impossible due to the sheer number of assets to be sighted. The main contribution of this paper is an overview of challenges and limitations encountered in the course of automated classification of image data. An introduction of state-of-the-art methods, including face-and skin tone detection, face-and texture recognition as well as craniofacial growth evaluation is provided. Based on a prototypical implementation of feasible and promising approaches, the performance is evaluated, as well as their abilities and shortcomings.

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“…The circularity of the human faces was used as a feature to detect, localize and distinguish human faces form other objects. Talele et al [8] has given a method in which brightness normalization is performed using histogram equalization method. Adaboost is a boosting technique which is used to select a small no of features and to design strong classifier.…”

Section: Related Workmentioning

confidence: 99%

Mingle Face Detection using Adaptive Thresholding and Hybrid Median Filter

Kaur¹

2013

IJCA

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Face detection has many applications in the field of digital image processing like face recognition, face analysis etc. Various techniques have been proposed so far to detect faces in images by different researchers. This paper presents a noble face detection algorithm which integrates the adaptive segmentation and hybrid median filter to improve the performance of face detection algorithms. Single faces noisy images are considered in this research work to evaluate the performance of the proposed algorithm. The results are compared with some well known face detection algorithms.

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Face detection and geometric face normalization

Cited by 14 publications

References 6 publications

Comparative Survey of Face Recognition Techniques

Comparative Survey of Face Recognition Techniques

Challenges and Limitations Concerning Automatic Child Pornography Classification

Mingle Face Detection using Adaptive Thresholding and Hybrid Median Filter

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