: Bir Bhanu, Ju Han
: Human Recognition at a Distance in Video
: Springer-Verlag
: 9780857291240
: Advances in Computer Vision and Pattern Recognition
: 1
: CHF 87.00
:
: Anwendungs-Software
: English
: 253
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF

Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera.

This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are acquired from a distance. It examines both model-free and model-based approaches to gait-based human recognition, including newly developed techniques where the both the model and the data (obtained from multiple cameras) are in 3D. In addition, the work considers new video-based techniques for face profile recognition, and for the super-resolution of facial imagery obtained at different angles. Finally, the book investigates integrated systems that detect and fuse both gait and face biometrics from video data.

Topics and features: discusses a framework for human gait analysis based on Gait Energy Image, a spatio-temporal gait representation; evaluates the discriminating power of model-based gait features using Bayesian statistical analysis; examines methods for human recognition using 3D gait biometrics, and for moving-human detection using both color and thermal image sequences; describes approaches for the integration face profile and gait biometrics, and for super-resolution of frontal and side-view face images; introduces an objective non-reference quality evaluation algorithm for super-resolved images; presents performance comparisons between different biometrics and different fusion methods for integrating gait and super-resolved face from video.

This unique and authoritative text is an invaluable resource for researchers and graduate students of computer vision, pattern recognition and biometrics. The book will also be of great interest to professional engineers of biometric systems.

Preface5
Contents8
List of Figures13
List of Tables21
Introduction to Gait-Based Individual Recognition at a Distance24
Introduction25
Gait-Based Human Recognition26
Face-Based Human Recognition26
Key Ideas Described in the Book27
Organization of the Book29
Gait-Based Individual Recognition at a Distance32
Gait Representations in Video33
Human Motion Analysis and Representations33
Human Activity and Individual Recognition by Gait34
Human Recognition by Gait35
Model-Based Approaches35
Model-Free Approaches35
Human Activity Recognition37
Model-Based Approaches37
Model-Free Approaches37
Gait Energy Image (GEI) Representation37
Motivation38
Representation Construction38
Relationship with MEI and MHI38
Representation Justification39
Framework for GEI-Based Recognition41
Silhouette Extraction and Processing41
Feature Extraction42
Summary44
Model-Free Gait-Based Human Recognition in Video45
Statistical Feature Fusion for Human Recognition by Gait45
Real and Synthetic Gait Templates46
Human Recognition48
Experimental Results50
Data and Parameters50
Performance Evaluation52
Human Recognition Based on Environmental Context53
Walking Surface Type Detection54
Classifier Design57
Probabilistic Classifier Combination58
Experimental Results59
View-Insensitive Human Recognition by Gait60
View-Insensitive Gait Templates60
Human Recognition62
Experimental Results63
Human Repetitive Activity Recognition in Thermal Imagery65
Object Detection in Thermal Infrared Imagery66
Human Repetitive Activity Representation and Recognition67
Experimental Results68
Human Recognition Under Different Carrying Conditions70
Technical Approach70
Gait Energy Image (GEI)70
Feature Extraction71
Co-evolutionary Genetic Programming72
Majority Voting73
Experimental Results73
Data73
Experiments74
Classifier Performance Comparison74
Summary75
Discrimination Analysis for Model-Based Gait Recognition77
Predicting Human Recognition Performance77
Algorithm Dependent Prediction and Performance Bounds78
Body Part Length Distribution78
Algorithm Dependent Performance Prediction80
Upper Bound on PCR81
Experimental Results82
Summary83
Model-Based Human Recognition-2D and 3D Gait85
2D Gait Recognition (3D Model, 2D Data)85
3D Human Modeling86
Human Kinematic Model86
Human Model Parameter Selection87
Camera Model and Coordinate Transformation88
World Coordinate to Camera Coordinate89
Camera Coordinate to Ideal Image Coordinate89
Ideal Image Coordinate to Actual Image Coordinate89
Actual Image Coordinate to Computer Image Coordinate90
Human Recognition from Single Non-calibrated Camera90
Silhouette Preprocessing90
Matching Between 3D Model and 2D Silhouette91
Human Model Parameter Estimation91
Stationary Parameter Estimation91