 Springer (11-2010) | PDF | 261 pages | 0857291238 | 13.6Mb Human Recognition at a Distance in Video /by Bir Bhanu and Ju Han. 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 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 of 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 download link:
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