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3D Face Recognition System Based on 3D Eigenfaces

2013
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Release : 2013
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Kind : eBook
Book Rating : 197/5 ( reviews)

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Book Synopsis 3D Face Recognition System Based on 3D Eigenfaces by : Divyarajsinh Parmar

Download or read book 3D Face Recognition System Based on 3D Eigenfaces written by Divyarajsinh Parmar. This book was released on 2013. Available in PDF, EPUB and Kindle. Book excerpt: A face recognition system that solves the problem of changes in facial expression and mimics in 3D range images. So here, we propose a local variation detection and restoration method based eigenfaces using the principal component analysis (PCA). The depth map of a 3D facial image is first smoothed using median filter to minimize the local variation. The forefront nose point is selected to be the image center for alignment. The detected face shape is cropped & normalized to a standard image size of 101x101 pixels. Facial depth-valus are scaled between 0 and 255 for translation and scaling-invariant identification. The preprocessed face image is smoothed to minimize the local variations. The PCA is applied to the resultant range data and the corresponding principal or Eigen images are used as the characteristic feature vectors of the subject to find the person identity in the database of pre-recorded faces. The system performance is tested on the GavabDB databases. Experimental results show that the proposed method is able to identify subjects with different facial expression and mimics in the presence of noise in their 3D facial images.

Efficient 3D face recognition based on PCA

2012-11-05 Computers
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Release : 2012-11-05
Genre : Computers
Kind : eBook
Book Rating : 340/5 ( reviews)

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Book Synopsis Efficient 3D face recognition based on PCA by : Yagnesh Parmar

Download or read book Efficient 3D face recognition based on PCA written by Yagnesh Parmar. This book was released on 2012-11-05. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2012 in the subject Engineering - Computer Engineering, Gujarat University, course: Electronics and communication, language: English, abstract: This thesis describes a face recognition system that overcomes the problem of changes in gesture and mimics in three-dimensional (3D) range images. Here, we propose a local variation detection and restoration method based on the two-dimensional (2D) principal component analysis (PCA). The depth map of a 3D facial image is first smoothed using median filter to minimize the local variation. The detected face shape is cropped & normalized to a standard image size of 101x101 pixels and the forefront nose point is selected to be the image center. Facial depthvalues are scaled between 0 and 255 for translation and scaling-invariant identification. The preprocessed face image is smoothed to minimize the local variations. The 2DPCA is applied to the resultant range data and the corresponding principal-(or eigen-) images are used as the characteristic feature vectors of the subject to find his/her identity in the database of pre-recorded faces. The system's performance is tested against the GavabDB facial databases. Experimental results show that the proposed method is able to identify subjects with different gesture and mimics in the presence of noise in their 3D facial image.

Face Recognition in Adverse Conditions

2014-04-30 Computers
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Release : 2014-04-30
Genre : Computers
Kind : eBook
Book Rating : 67X/5 ( reviews)

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Book Synopsis Face Recognition in Adverse Conditions by : De Marsico, Maria

Download or read book Face Recognition in Adverse Conditions written by De Marsico, Maria. This book was released on 2014-04-30. Available in PDF, EPUB and Kindle. Book excerpt: Facial recognition software has improved by leaps and bounds over the past few decades, with error rates decreasing significantly within the past ten years. Though this is true, conditions such as poor lighting, obstructions, and profile-only angles have continued to persist in preventing wholly accurate readings. Face Recognition in Adverse Conditions examines how the field of facial recognition takes these adverse conditions into account when designing more effective applications by discussing facial recognition under real world PIE variations, current applications, and the future of the field of facial recognition research. The work is intended for academics, engineers, and researchers specializing in the field of facial recognition.

3D Face Recognition Using PCA

2012-04
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Release : 2012-04
Genre :
Kind : eBook
Book Rating : 014/5 ( reviews)

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Book Synopsis 3D Face Recognition Using PCA by : Yagnesh Parmar

Download or read book 3D Face Recognition Using PCA written by Yagnesh Parmar. This book was released on 2012-04. Available in PDF, EPUB and Kindle. Book excerpt: This book describes a face recognition system that overcomes the problem of changes in gesture and mimics in three-dimensional (3D) range images. Here, we propose a local variation detection and restoration method based on the two-dimensional (2D) principal component analysis (PCA). The depth map of a 3D facial image is first smoothed using median filter to minimize the local variation. The detected face shape is cropped & normalized to a standard image size of 101x101 pixels and the forefront nose point is selected to be the image center. Facial depth-values are scaled between 0 and 255 for translation and scaling-invariant identification. The preprocessed face image is smoothed to minimize the local variations. The 2DPCA is applied to the resultant range data and the corresponding principal-(or eigen-) images are used as the characteristic feature vectors of the subject to find his/her identity in the database of pre-recorded faces. The system's performance is tested against the GavabDB facial databases. Experimental results show that the proposed method is able to identify subjects with different gesture and mimics in the presence of noise in their 3D facial images.

Face Detection and Modeling for Recognition

2002 Biometry
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Release : 2002
Genre : Biometry
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Face Detection and Modeling for Recognition by : Rein-Lien Hsu

Download or read book Face Detection and Modeling for Recognition written by Rein-Lien Hsu. This book was released on 2002. Available in PDF, EPUB and Kindle. Book excerpt: Face recognition has received substantial attention from researchers in biometrics, computer vision, pattern recognition, and cognitive psychology communities because of the increased attention being devoted to security, man-machine communication, content-based image retrieval, and image/video coding. We have proposed two automated recognition paradigms to advance face recognition technology. Three major tasks involved in face recognition systems are: (i) face detection, (ii) face modeling, and (iii) face matching. We have developed a face detection algorithm for color images in the presence of various lighting conditions as well as complex backgrounds. Our detection method first corrects the color bias by a lighting compensation technique that automatically estimates the parameters of reference white for color correction. We overcame the difficulty of detecting the low-luma and high-luma skin tones by applying a nonlinear transformation to the Y CbCr color space. Our method generates face candidates based on the spatial arrangement of detected skin patches. We constructed eye, mouth, and face boundary maps to verify each face candidate. Experimental results demonstrate successful detection of faces with different sizes, color, position, scale, orientation, 3D pose, and expression in several photo collections. 3D human face models augment the appearance-based face recognition approaches to assist face recognition under the illumination and head pose variations. For the two proposed recognition paradigms, we have designed two methods for modeling human faces based on (i) a generic 3D face model and an individual's facial measurements of shape and texture captured in the frontal view, and (ii) alignment of a semantic face graph, derived from a generic 3D face model, onto a frontal face image.

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