Parallel Architecture for Face Recognition using MPI
TL;DR: Two different parallel architectures are proposed to accelerate training and testing phases of PCA algorithm by exploiting the benefits of distributed memory architecture and achieve linear speed-up and system scalability on different data sizes from the Facial Recognition Technology database.
read more
Abstract: The face recognition applications are widely used in different fields like security and computer vision. The recognition process should be done in real time to take fast decisions. Princi-ple Component Analysis (PCA) considered as feature extraction technique and is widely used in facial recognition applications by projecting images in new face space. PCA can reduce the dimensionality of the image. However, PCA consumes a lot of processing time due to its high intensive computation nature. Hence, this paper proposes two different parallel architectures to accelerate training and testing phases of PCA algorithm by exploiting the benefits of distributed memory architecture. The experimental results show that the proposed architectures achieve linear speed-up and system scalability on different data sizes from the Facial Recognition Technology (FERET) database.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Hybrid MPI/OpenMP implementation of PCA
Dalia Shouman Ibrahim,Salma Hamdy +1 more
- 05 Dec 2017
TL;DR: The proposed approaches focus on data partitioning to minimize the execution time of the algorithm by distributing data over a cluster with parallel computing architecture.
3
Performance Analysis of Parallel Implementation of PCA-based Face Recognition using OpenCL
S. Sapna,R Anjali,Shobha N Kamath +2 more
- 17 May 2019
TL;DR: Parallel implementation of PCA based face recognition is parallelized using OpenCL to speed up the computation and a comparison is made in terms of computational time required for serial and parallel implementation.
1
Towards large-scale face-based race classification on spark framework
TL;DR: A new large-scale race classification method which combines Local Binary Pattern (LBP) and Logistic Regression (LR) on Spark framework which achieves the highest race classification accuracy (99.99%) compared to Linear SVM, Naive Bayesian (NB), Random Forest(RF), and Decision Tree (DT) Spark’s classifiers.
Multiple-Face Recognition Using Parallel Computing - a Review
Vijaykumar Mantri,Yogesh Deshpande +1 more
- 01 Jan 2023
TL;DR: Multiple-face recognition using parallel computing - a review. This paper reviews research on improving multi-face detection results using parallel computing frameworks and methods.
References
The FERET evaluation methodology for face-recognition algorithms
TL;DR: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems.
5.1K
The FERET evaluation methodology for face-recognition algorithms
P.J. Phillips,Hyeonjoon Moon,Patrick J. Rauss,Syed A. Rizvi +3 more
- 17 Jun 1997
TL;DR: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems.
3.9K
Two-dimensional PCA: a new approach to appearance-based face representation and recognition
TL;DR: A new technique coined two-dimensional principal component analysis (2DPCA) is developed for image representation that is based on 2D image matrices rather than 1D vectors so the image matrix does not need to be transformed into a vector prior to feature extraction.
A high-performance, portable implementation of the MPI message passing interface standard
William Gropp,Ewing Lusk,Nathan E. Doss,Anthony Skjellum +3 more
- 01 Sep 1996
TL;DR: The MPI Message Passing Interface (MPI) as mentioned in this paper is a standard library for message passing that was defined by the MPI Forum, a broadly based group of parallel computer vendors, library writers, and applications specialists.
2.4K
Portable implementation of the mpi message passing interface standard
William Gropp,Ewing Lusk,Nathan E. Doss,A. Skjeltum. A Highperformance +3 more
- 01 Jan 1996
TL;DR: The MPI Message Passing Interface (MPI) as discussed by the authors is a standard library for message passing that was defined by the MPI Forum, a broadly based group of parallel computer vendors, library writers, and applications specialists.
2K