H
Harry Wechsler
Researcher at George Mason University
Publications - 267
Citations - 15883
Harry Wechsler is an academic researcher from George Mason University. The author has contributed to research in topics: Facial recognition system & FERET database. The author has an hindex of 50, co-authored 267 publications receiving 15056 citations. Previous affiliations of Harry Wechsler include Hewlett-Packard & University of Wisconsin–Milwaukee.
Papers
More filters
Journal ArticleDOI
The FERET database and evaluation procedure for face-recognition algorithms
TL;DR: The FERET evaluation procedure is an independently administered test of face-recognition algorithms to allow a direct comparison between different algorithms and to assess the state of the art in face recognition.
Journal ArticleDOI
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition
Chengjun Liu,Harry Wechsler +1 more
TL;DR: Zhang et al. as discussed by the authors introduced a novel Gabor-Fisher (1936) classifier (GFC) for face recognition, which is robust to changes in illumination and facial expression, applies the enhanced Fisher linear discriminant model (EFM) to an augmented Gabor feature vector derived from the Gabor wavelet representation of face images.
Journal ArticleDOI
Micro-Doppler effect in radar: phenomenon, model, and simulation study
TL;DR: In this paper, the micro-Doppler effect was introduced in radar data, and a model of Doppler modulations was developed to derive formulas of micro-doppler induced by targets with vibration, rotation, tumbling and coning motions.
Journal ArticleDOI
Tracking Groups of People
TL;DR: A computer vision system for tracking multiple people in relatively unconstrained environments is described and should provide a useful mechanism for bootstrapping and reinitialization of tracking using more specific but less robust human models.
Journal ArticleDOI
Independent component analysis of Gabor features for face recognition
Chengjun Liu,Harry Wechsler +1 more
TL;DR: An independent Gabor features (IGFs) method and its application to face recognition is presented, which achieves 98.5% correct face recognition accuracy when using 180 features for the FERET dataset, and 100% accuracy for the ORL dataset using 88 features.