Face Detection and Recognition in Indoor Environment
Author | : |
Publisher | : |
Total Pages | : 52 |
Release | : 2007 |
Genre | : |
ISBN | : |
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Author | : |
Publisher | : |
Total Pages | : 52 |
Release | : 2007 |
Genre | : |
ISBN | : |
Author | : Sumesh Kunwar |
Publisher | : |
Total Pages | : |
Release | : 2016 |
Genre | : |
ISBN | : |
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.
Author | : Kamal Adel Abuqaaud |
Publisher | : |
Total Pages | : 109 |
Release | : 2013 |
Genre | : Biometric identification |
ISBN | : |
"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.
Author | : Thirimachos Bourlai |
Publisher | : Springer |
Total Pages | : 388 |
Release | : 2016-02-12 |
Genre | : Computers |
ISBN | : 3319285017 |
This authoritative text/reference presents a comprehensive review of algorithms and techniques for face recognition (FR), with an emphasis on systems that can be reliably used in operational environments. Insights are provided by an international team of pre-eminent experts into the processing of multispectral and hyperspectral face images captured under uncontrolled environments. These discussions cover a variety of imaging sensors ranging from state-of-the-art visible and infrared imaging sensors, to RGB-D and mobile phone image sensors. A range of different biometric modalities are also examined, including face, periocular and iris. This timely volume is a mine of useful information for researchers, practitioners and students involved in image processing, computer vision, biometrics and security.
Author | : Asit Kumar Datta |
Publisher | : CRC Press |
Total Pages | : 353 |
Release | : 2015-10-28 |
Genre | : Computers |
ISBN | : 148222657X |
Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver's license issuance, law enforcement investigations, and physical access control.Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face de
Author | : Stan Z. Li |
Publisher | : Springer Science & Business Media |
Total Pages | : 394 |
Release | : 2005-12-06 |
Genre | : Computers |
ISBN | : 0387272577 |
Although the history of computer-aided face recognition stretches back to the 1960s, automatic face recognition remains an unsolved problem and still offers a great challenge to computer-vision and pattern recognition researchers. This handbook is a comprehensive account of face recognition research and technology, written by a group of leading international researchers. Twelve chapters cover all the sub-areas and major components for designing operational face recognition systems. Background, modern techniques, recent results, and challenges and future directions are considered. The book is aimed at practitioners and professionals planning to work in face recognition or wanting to become familiar with the state-of- the-art technology. A comprehensive handbook, by leading research authorities, on the concepts, methods, and algorithms for automated face detection and recognition. Essential reference resource for researchers and professionals in biometric security, computer vision, and video image analysis.
Author | : Stan Z. Li |
Publisher | : Springer Nature |
Total Pages | : 473 |
Release | : 2024-01-30 |
Genre | : Computers |
ISBN | : 3031435672 |
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.
Author | : Mohamed Kamel |
Publisher | : Springer |
Total Pages | : 428 |
Release | : 2011-06-14 |
Genre | : Computers |
ISBN | : 3642215963 |
The two-volume set LNCS 6753/6754 constitutes the refereed proceedings of the 8th International Conference on Image and Recognition, ICIAR 2011, held in Burnaby, Canada, in June 2011. The 84 revised full papers presented were carefully reviewed and selected from 147 submissions. The papers are organized in topical sections on image and video processing; feature extraction and pattern recognition; computer vision; color, texture, motion and shape; tracking; biomedical image analysis; biometrics; face recognition; image coding, compression and encryption; and applications.
Author | : Kresimir Delac |
Publisher | : BoD – Books on Demand |
Total Pages | : 250 |
Release | : 2008-12-01 |
Genre | : Computers |
ISBN | : 9537619346 |
The main idea and the driver of further research in the area of face recognition are security applications and human-computer interaction. Face recognition represents an intuitive and non-intrusive method of recognizing people and this is why it became one of three identification methods used in e-passports and a biometric of choice for many other security applications. This goal of this book is to provide the reader with the most up to date research performed in automatic face recognition. The chapters presented use innovative approaches to deal with a wide variety of unsolved issues.
Author | : Jorge S. Marques |
Publisher | : Springer Science & Business Media |
Total Pages | : 713 |
Release | : 2005-05-23 |
Genre | : Computers |
ISBN | : 3540261532 |
The two-volume set LNCS 3522 and 3523 constitutes the refereed proceedings of the Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005, held in Estoril, Portugal in June 2005. The 170 revised full papers presented were carefully reviewed and selected from 292 submissions. The papers are organized in topical sections on computer vision, shape and matching, image and video processing, image and video coding, face recognition, human activity analysis, surveillance, robotics, hardware architectures, statistical pattern recognition, syntactical pattern recognition, image analysis, document analysis, bioinformatics, medical imaging, biometrics, speech recognition, natural language analysis, and applications.