An efficient method to detect facial fiducial points for face recognition

Arca, Stefano; Campadelli, Paola; Lanzarotti, Raffaella

doi:10.1109/icpr.2004.1334190

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…Many different techniques have been developed to automatically tag facial landmarks on a face [1,2,3,4]. These techniques achieve good results over good quality and frontal faces, but are still not good enough for the cases of having high variability and low quality images.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the variability of facial landmarks in a forensic scenario

Vera-Rodríguez

Tomé

Fiérrez

et al. 2013

2013 International Workshop on Biometrics and Forensics (IWBF)

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Esta es la versión de autor de la comunicación de congreso publicada en: This is an author produced version of a paper published in: ABSTRACTThis paper reports an study of the variability of facial landmarks in a forensic scenario. This variability is affected by two factors: on the one hand, the precision in which the landmarks are tagged (manually or automatically), and on the other hand some other variability factors such as the pose, expression, occlusions, etc. For this study, a mugshot database of 50 persons has been collected following the procedure used by the Spanish Guardia Civil. Mugshots are taken with three distances between the persons and the camera (3, 2, 1 meters) showing the full body, the upper body and the face respectively, obtaining in total 1200 images. 21 facial landmarks are defined and the database was manually tagged imitating the procedure followed by a forensic examiner. This paper analyses the facial landmarking variability for the three distances considered, and also considering the differences obtained for male and female. Results show that landmarks located in the outer part of the face (highest end of the head, ears and chin) present a higher level of variability compared to the landmarks located the inner face (eye region, and nose). Regarding the gender, the landmarks placed in the outer part of the face present a higher level of variability for women compared to men.

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Section: Introductionmentioning

confidence: 99%

Analysis of the variability of facial landmarks in a forensic scenario

Vera-Rodríguez

Tomé

Fiérrez

et al. 2013

2013 International Workshop on Biometrics and Forensics (IWBF)

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“…In this paper we present an authentication system in which the biometric characterization is similar to the one proposed in [2], while the identification is completely new. This authentication task corresponds to an "open-universe scenario" where persons unknown to the system may claim access.…”

Section: Introductionmentioning

confidence: 99%

“…In [1] we presented a method to determine robustly and efficiently the fiducial points associated to the eyebrows, the nose and the chin; regarding the eyes and the mouth we adopted the deformable template technique which estimates the whole features contour, but which is computationally very expensive. In [2] we proposed an efficient alternative for the eyes, based on the analysis of the edges obtained by means of the first derivative of Gaussian filters, while for the mouth we considered the mouth corners used for the template initialization and we derived the upper and lower middle points as a function of them. Moreover, we proposed a module able to recognize automatically which fiducial points have been wrongly determined, and which recovers them on the basis of the positions and dimensions of the reliable features.…”

Section: Introductionmentioning

confidence: 99%

“…In [2] we presented an identification system, which automatically localizes 19 fiducial points 1 and characterizes the face applying a bank of Gabor filters in correspondence to each fiducial point. In that case given a test image, the system computes its face characterization, and looks for in a gallery the subject who maximizes a suitably defined similarity function.…”

Section: Introductionmentioning

confidence: 99%

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An Automatic Feature Based Face Authentication System,

et al. 2006

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Abstract. In this paper a fully automatic face verification system is presented. A face is characterized by a vector (jet) of coefficients determined applying a bank of Gabor filters in correspondence to 19 facial fiducial points automatically localized. The identity claimed by a subject is accepted or rejected depending on a similarity measure computed among the jet characterizing the subject, and the ones corresponding to the subjects in the gallery. The performance of the system has been quantified according to the Lausanne evaluation protocol for authentication.

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“…Many different techniques have been developed to automatically tag facial landmarks on a face [1][2][3][4][5]. These techniques achieve good results over good quality and frontal faces, but are still not that good for the cases of having high variability and low quality images.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of the Variability of Facial Landmarks for Forensics Using CCTV Images

Vera-Rodríguez

Tomé

Fiérrez

et al. 2014

Image and Video Technology

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Esta es la versión de autor del congreso publicado en: This is an author produced version of a paper published in: Abstract. This paper reports a study of the variability of facial landmarks in a forensic scenario using images acquired from CCTV images. This type of images presents a very low quality and a large range of variability factors such as differences in pose, expressions, occlusions, etc. Apart from this, the variability of facial landmarks is affected by the precision in which the landmarks are tagged. This process can be done manually or automatically depending on the application (e.g., forensics or automatic face recognition, respectively). This study is carried out comparing both manual and automatic procedures, and also 3 distances between the camera and the subjects. Results show that landmarks located in the outer part of the face (highest end of the head, ears and chin) present a higher level of variability compared to the landmarks located the inner face (eye region, and nose). This study shows that the landmark variability increases with the distance between subject and camera, and also the results of the manual and automatic approaches are similar for the inner facial landmarks.

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An efficient method to detect facial fiducial points for face recognition

Cited by 6 publications

References 6 publications

Analysis of the variability of facial landmarks in a forensic scenario

Analysis of the variability of facial landmarks in a forensic scenario

An Automatic Feature Based Face Authentication System,

Comparative Analysis of the Variability of Facial Landmarks for Forensics Using CCTV Images

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