Part I: Introduction to Gait-based Individual Recognition at a Distance
Part II: Gait-based Individual Recognition at a Distance Gait Representations in Video
Model-free Gait-based Human Recognition in Video
Discrimination Analysis for Model-based Gait Recognition
Model-based Human Recognition: 2D and 3D Gait
Fusion of Color/Infrared Video for Human Detection
Part III: Face Recognition at a Distance in Video
Super-resolution of Facial Images in Video at a Distance
Evaluating Quality of Super-resolved Face Images
Part IV: Integrated Face and Gait for Human Recognition at a Distance in Video
Integrating Face Profile and Gait at a Distance
Match Score Level Fusion of Face and Gait at a Distance
Feature Level Fusion of Face and Gait at a Distance
Part V: Conclusions for Integrated Gait and Face for Human Recognition at a Distance in Video
Conclusions and Future Work
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 a
Addresses the fundamental problems associated with gait and face-based human recognition from video data acquired from a distanceExamines methods for human recognition using 3D gait biometrics, and for the super-resolution of facial imagery obtained at different anglesInvestigates integrated systems that detect and fuse both gait and face biometrics