3-D face recognition: features, databases, algorithms and challenges

Patil, Hemprasad Yashwant; Kothari, Ashwin; Bhurchandi, Kishor M.

doi:10.1007/s10462-015-9431-0

Cited by 64 publications

(33 citation statements)

References 159 publications

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“…They are considered as the most attractive areas for biometric schemes [29][30][31][32][33][34][35]. The unimodal face and iris system processing steps include preprocessing, feature extraction and producing matching scores.…”

Section: Unimodal Biometric Systemsmentioning

confidence: 99%

Optimal Face-Iris Multimodal Fusion Scheme

Sharifi

Eskandari

2016

Symmetry

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Multimodal biometric systems are considered a way to minimize the limitations raised by single traits. This paper proposes new schemes based on score level, feature level and decision level fusion to efficiently fuse face and iris modalities. Log-Gabor transformation is applied as the feature extraction method on face and iris modalities. At each level of fusion, different schemes are proposed to improve the recognition performance and, finally, a combination of schemes at different fusion levels constructs an optimized and robust scheme. In this study, CASIA Iris Distance database is used to examine the robustness of all unimodal and multimodal schemes. In addition, Backtracking Search Algorithm (BSA), a novel population-based iterative evolutionary algorithm, is applied to improve the recognition accuracy of schemes by reducing the number of features and selecting the optimized weights for feature level and score level fusion, respectively. Experimental results on verification rates demonstrate a significant improvement of proposed fusion schemes over unimodal and multimodal fusion methods.

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Section: Unimodal Biometric Systemsmentioning

confidence: 99%

Optimal Face-Iris Multimodal Fusion Scheme

Sharifi

Eskandari

2016

Symmetry

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“…The drawbacks hindered the feasible implementation of a stereo vision system, hence the ideal properties, such as having communication with no time delay, or having curved camera chips, as well as displays which gave a distortion-less, extended field of view were unattainable. The studies affirm that implementing the stereo vision telepresence system will in effect lead to realising the ideal properties of stereo vision systems [42], [43]. The available components of the planar camera display and chips that are used for displaying and capturing were typically from the NTSC standard video [44].…”

Section: B Discussionmentioning

confidence: 68%

3D Face Tracking Using Stereo Cameras: A Review

et al. 2020

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This review considers previous research, regarding the background and applications of 3D facetracking systems with a focus on stereo camera-based systems. Stereo cameras are less expensive than laser ranging systems, and they are widely available on devices such as smart phones. This review aims to spur further development and applications of face tracking in this domain. Many studies on face tracking have used concepts such as the Kanade-Lucas-Tomasi method, particle filters, tracking-learning-detecting, probability hypothesis density, mean shift/cam shift, and others. As imaging constraints are relaxed, facial tracking becomes more challenging. This review presents an exposition of the most common challenges in face tracking, such as occlusion and clutter, pose variations, changes in facial resolution, illumination variations, and facial deformation. Five forms of pose estimation are discussed: appearance template methods, detector arrays, flexible models, geometric methods, and tracking methods. Applications of the listed 3D face tracking systems are also discussed, including face modelling, film editing, access control, security, and surveillance.

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“…Due to pose, expression, makeup variation in 2D (Two-Dimensional) face recognition suffers from poor identification in spite of broad research. The recognition of face using 3D facial surface and shape has increased the discriminating features due to increased dimensionality [11].…”

Section: Exhaustive Security System Based On Face Recognition Incorpomentioning

confidence: 99%

Exhaustive Security System Based on Face Recognition Incorporated with Number Plate Identification using Optical Character Recognition

Zaheen

Mohi-u-din

Siddique

et al. 2020

Mehran Univ. res. j. eng. technol.

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In recent times due to rise in terrorism, people need to live in a safer place where unidentified persons will not be allowed to enter in the premises. Securing of major areas is a vital issue that needs to be addressed for the intelligence and security agencies. At the surrounding of premises, CCTV (CloseCircuit Television) cameras are usually installed to identify the number plate from database by using OCR (Optical Character Recognition) algorithm. This method of security by identifying only vehicle without verifying the person inside it is usually causing serious security issues. Identification of a person is usually done through image processing by using Viola Jones algorithm and acquire the information of the facial components to create a dataset for machine learning. It is imperative to introduce such a system that will be capable to identify the person along with the number plate of vehicle from the stored database. In this research, a comprehensive security system based on face recognition integrated with the vehicle number plate is proposed. The combined information of both dedicated cameras is then transferred to the based station for identification. This system is capable, of securing premises from crime in a more enhanced way.

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3-D face recognition: features, databases, algorithms and challenges

Cited by 64 publications

References 159 publications

Optimal Face-Iris Multimodal Fusion Scheme

Optimal Face-Iris Multimodal Fusion Scheme

3D Face Tracking Using Stereo Cameras: A Review

Exhaustive Security System Based on Face Recognition Incorporated with Number Plate Identification using Optical Character Recognition

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