Title
Face recognition through learning boundary characteristics
Abstract
This paper presents a new approach to face recognition, combining the techniques of computer vision and machine learning. A steady improvement in recognition performance is demonstrated. It is achieved by learning individual faces in terms of the local shapes of image boundaries. High-level facial features, such as nose, are not explicitly used in this scheme. Several machine learning methods are tested and compared. The overall objectives are formulated as follows: Classify the different tasks of "face recognition" and suggest an orderly terminology to distinguish between them. Design a set of easily and reliably obtainable descriptors and their automatic extraction from the images. Compare plausible machine learning methods; tailor them to this domain. Design experiments that would best reflect the needs of real world applications, and suggest a general methodology for further research. Perform the experiments and compare the performance.
Year
DOI
Venue
1994
10.1080/08839519408945436
APPLIED ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
face recognition,machine learning
Facial recognition system,Terminology,Computer science,Image processing,Feature (machine learning),Artificial intelligence,Quantization (signal processing),Machine learning
Journal
Volume
Issue
ISSN
8
1
0883-9514
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Libor Spacek19815.73
Miroslav Kubat22384231.57
Doris Flotzinger34616.76