Determination of the most representative descriptor among a set of feature vectors for the same object

07/06/2020
by   Dmitry Pozdnyakov, et al.
0

On an example of solution of the face recognition problem the approach for estimation of the most representative descriptor among a set of feature vectors for the same face is considered in present study. The estimation is based on robust calculation of the mode-median mixture vector for the set as the descriptor by means of Welsch/Leclerc loss function application in case of very sparse filling of the feature space with feature vectors

READ FULL TEXT

page 6

page 7

page 8

research
05/21/2010

Reduction of Feature Vectors Using Rough Set Theory for Human Face Recognition

In this paper we describe a procedure to reduce the size of the input fe...
research
12/10/2021

Hyperdimensional Feature Fusion for Out-Of-Distribution Detection

We introduce powerful ideas from Hyperdimensional Computing into the cha...
research
07/24/2018

Multicolumn Networks for Face Recognition

The objective of this work is set-based face recognition, i.e. to decide...
research
01/03/2022

Local Directional Gradient Pattern: A Local Descriptor for Face Recognition

In this paper a local pattern descriptor in high order derivative space ...
research
10/26/2012

3D Face Recognition using Significant Point based SULD Descriptor

In this work, we present a new 3D face recognition method based on Speed...
research
04/13/2015

Multiple Measurements and Joint Dimensionality Reduction for Large Scale Image Search with Short Vectors - Extended Version

This paper addresses the construction of a short-vector (128D) image rep...

Please sign up or login with your details

Forgot password? Click here to reset