Keywords
Kernel (algebra)CorrelationPattern recognition (psychology)Class (philosophy)Computer scienceMathematicsFilter (signal processing)Artificial intelligenceAlgorithmComputer visionDiscrete mathematics
Affiliated Institutions
Related Publications
Input space versus feature space in kernel-based methods
This paper collects some ideas targeted at advancing our understanding of the feature spaces associated with support vector (SV) kernel functions. We first discuss the geometry ...
Recognizing imprecisely localized, partially occluded, and expression variant faces from a single sample per class
The classical way of attempting to solve the face (or object) recognition problem is by using large and representative data sets. In many applications, though, only one sample p...
Wavelet transform methods for object detection and recovery
We show that a biorthogonal spline wavelet closely approximates the prewhitening matched filter for detecting Gaussian objects in Markov noise. The filterbank implementation of ...
Mean shift: a robust approach toward feature space analysis
A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational...
Face recognition using the nearest feature line method
In this paper, we propose a novel classification method, called the nearest feature line (NFL), for face recognition. Any two feature points of the same class (person) are gener...
Publication Info
- Year
- 2005
- Type
- book-chapter
- Pages
- 32-43
- Citations
- 42
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
42
OpenAlex
Cite This
Chunyan Xie,
Marios Savvides,
B. V. K. Vijaya Kumar
(2005).
Kernel Correlation Filter Based Redundant Class-Dependence Feature Analysis (KCFA) on FRGC2.0 Data.
Lecture notes in computer science
, 32-43.
https://doi.org/10.1007/11564386_4
Identifiers
- DOI
- 10.1007/11564386_4