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Face Recognition in Uncontrolled Indoor Environment

Face Recognition in Uncontrolled Indoor Environment
Author: Kamal Adel Abuqaaud
Publisher:
Total Pages: 109
Release: 2013
Genre: Biometric identification
ISBN:
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"Face recognition (FR) is one of the most convenient biometric systems even though it is not currently the most reliable one. Especially when images for (FR) system are captured by surveillance cameras, such cameras often produce low quality images which make recognition more difficult and less reliable. This study uses a recently published database called 'SCface database' which emphasizes the challenges of face recognition in uncontrolled indoor conditions such as lighting conditions, face pose, facial expression and distance to camera. More specifically, the recognition is done using different cameras of different resolutions and imaging sensors. The aim of this study is to examine the effect of camera quality and distance from the camera with regards to face recognition rates by analyzing different face recognition schemes such as Eigenfaces, Discrete Cosine Transform (DCT), Wavelet Transform, Gray Level Concurrence Matrix (GLCM) and Spatial Differential Operators (SDO). Principal Component Analysis (PCA), Zonal coding and spectral regression were also investigated as various dimensionality reduction approaches"--Abstract.

Face Recognition in Adverse Conditions

Face Recognition in Adverse Conditions
Author: De Marsico, Maria
Publisher: IGI Global
Total Pages: 506
Release: 2014-04-30
Genre: Computers
ISBN: 146665967X
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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.

Advances in Visual Computing

Advances in Visual Computing
Author: George Bebis
Publisher: Springer Nature
Total Pages: 718
Release: 2019-10-25
Genre: Computers
ISBN: 3030337200
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This book constitutes the refereed proceedings of the 14th International Symposium on Visual Computing, ISVC 2019, held in Lake Tahoe, NV, USA in October 2019. The 100 papers presented in this double volume were carefully reviewed and selected from 163 submissions. The papers are organized into the following topical sections: Deep Learning I; Computer Graphics I; Segmentation/Recognition; Video Analysis and Event Recognition; Visualization; ST: Computational Vision, AI and Mathematical methods for Biomedical and Biological Image Analysis; Biometrics; Virtual Reality I; Applications I; ST: Vision for Remote Sensing and Infrastructure Inspection; Computer Graphics II; Applications II; Deep Learning II; Virtual Reality II; Object Recognition/Detection/Categorization; and Poster.

Human Recognition in Unconstrained Environments

Human Recognition in Unconstrained Environments
Author: Maria De Marsico
Publisher: Academic Press
Total Pages: 250
Release: 2017-01-09
Genre: Computers
ISBN: 0081007124
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Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities

Face Analysis Under Uncontrolled Conditions

Face Analysis Under Uncontrolled Conditions
Author: Romain Belmonte
Publisher: John Wiley & Sons
Total Pages: 325
Release: 2022-10-18
Genre: Computers
ISBN: 1789451116
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Face analysis is essential for a large number of applications such as human-computer interaction or multimedia (e.g. content indexing and retrieval). Although many approaches are under investigation, performance under uncontrolled conditions is still not satisfactory. The variations that impact facial appearance (e.g. pose, expression, illumination, occlusion, motion blur) make it a difficult problem to solve. This book describes the progress towards this goal, from a core building block – landmark detection – to the higher level of micro and macro expression recognition. Specifically, the book addresses the modeling of temporal information to coincide with the dynamic nature of the face. It also includes a benchmark of recent solutions along with details about the acquisition of a dataset for such tasks.

Handbook of Face Recognition

Handbook of Face Recognition
Author: Stan Z. Li
Publisher: Springer Nature
Total Pages: 473
Release: 2024-01-30
Genre: Computers
ISBN: 3031435672
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The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions. This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systems Provides comprehensive coverage of face detection, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applications Contains numerous step-by-step algorithms Describes a broad range of applications from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry.

Human Detection and Face Recognition in Indoor Environment to Improve Human-robot Interaction in Assistive and Collaborative Robots

Human Detection and Face Recognition in Indoor Environment to Improve Human-robot Interaction in Assistive and Collaborative Robots
Author: Sumesh Kunwar
Publisher:
Total Pages:
Release: 2016
Genre:
ISBN:
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Human detection in indoor environment is essential for Robots working together with humans in collaborative manufacturing environment. Similarly, Human detection is essential for service robots providing service with household chores or helping elderly population with different daily activities. Human detection can be achieved by Human Head detection, as head is the most discriminative part of human. Head detection method can be divided into three types: i) Method based on color mode; ii) Method based on template matching; and iii) Method based on contour detection. Method based on color mode is simple but is error prone. Method based on head template detects head in the image by searching for a template which is similar to head template. On the other hand, Method based on contour detection uses some information to describe head or head and shoulder information. The use of only one criteria may not be sufficient and accuracy of human head detection can be increased by combining the shape and color information. In this thesis, a method of human detection is proposed by combining the head shape and skin color (i.e., Combination of method based on Color mode and method based on Contour detection). Mainly, curvature criteria is used to segment out curves having similar curvature to find human head. Further, skin color is detected to localize face in image plane. A curve represents human head curve if only it has sufficient skin colored pixel in its closed proximity. Thus, by using color and human head curvature it was found that promising results could be obtained in human detection in indoor environment. iv After detecting humans in the surrounding, the next step for the robot could be to identify and recognize them. In this thesis, the use of Gabor filter response on nine points was investigated to identify eight different individuals. This suggests that the Gabor filter on nine points could be applied to identify people in small areas, for example home or small office with less individuals.