Computerized Face Detection and Recognition
Vytautas Perlibakas
Abstract
This publication presents methods for face detection, analysis and recognition: fast normalized cross-correlation (fast correlation coefficient) between multiple templates based face pre-detection method, method for detection of exact face contour based on snakes and Generalized Gradient Vector Flow field, method for combining recognition algorithms based on Cumulative Match Characteristics in order to increase recognition speed and accuracy, and face recognition method based on Principal Component Analysis of the Wavelet Packet Decomposition allowing to use PCA - based recognition method with large number of training images. For all the methods are presented experimental results and comparisons of speed and accuracy with large face databases.
Create a lesson
Related papers
FlowSGS: Improving Flow Matching Priors for Inverse Imaging with Stochastic Interpolants
Tianao Li, Xinhui Qian, Emma Alexander
Should This Case Be Adapted? Prediction Fragmentation Controls Test-Time Adaptation
Lili Wang, Jing Li, Xiaowen Sun et al.
FunArt: Decoding Functional Structure and Articulation from Generative 3D Latents
Dennis Rotondi, Abdelrhman Werby, Kai O. Arras
Earth Surface Immune System for Rapid Monitoring of Unknown Anomalies
Jingtao Li, Qian Zhu, Xinyu Wang et al.
PROVIA: Procedure State Tracking for Online Mistake Detection in Egocentric Videos
Di Wen, Kailun Yang, Jimmy Weissert et al.
Refinement Is Inherently Editable: Training-Free Prompt-to-Prompt Image Editing with Generative Refinement Network
Yulong Chen, Ziqian Zhang, Haoyu Zhang et al.