A new approach for small sample face recognition with pose variation by fusing Gabor encoding features and deep features

Zou, Guofeng; Fu, Guixia; Gao, Mingliang; Pan, Jinfeng; Liu, Zheng

doi:10.1007/s11042-020-09076-1

Cited by 15 publications

(8 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this process, some high-tech means need to be used, such as using cell phones or computers with cameras installed on them to collect data, or placing cameras directly in the human radiation area to collect intelligence information and analyze and process it, and then transmit it back to the monitoring host [7]. Or GPS positioning technology is used to obtain information related to personnel inside the university as well as documents and image data uploaded with external communication platforms, which can make it easier to manage the epidemic in the university [8].…”

Section: Face Recognition Technology Based On Open CVmentioning

confidence: 99%

Application and Management of College Epidemic Prevention and Control Information Platform Based on Face Recognition and Temperature Measurement Technology

2022

AJCIS

View full text Add to dashboard Cite

With the development of science and technology, computer science is becoming more and more mature and plays an important role in social life and economic development. Based on this background, an epidemic prevention and control information platform for universities based on face recognition technology and temperature technology has been created. The system can realize real-time monitoring of students' identity verification, ID card numbers and internal school item files, it can also effectively detect the body temperature of teachers and students, and make timely early warning suggestions to relevant departments based on the detection results, which provides effective data support as well as technical guarantee in public security work. At the same time, it uses embedded computer technology to realize the interaction of data between each link in the epidemic prevention work and the database, which is convenient for the staff to grasp the relevant data information and dynamic changes in a timely manner, thus providing effective guarantee measures for the management of universities. This paper introduces the information platform of university epidemic prevention and control based on face recognition and temperature recognition technology, and designs and implements the study of the system.

show abstract

Section: Face Recognition Technology Based On Open CVmentioning

confidence: 99%

Application and Management of College Epidemic Prevention and Control Information Platform Based on Face Recognition and Temperature Measurement Technology

2022

AJCIS

View full text Add to dashboard Cite

show abstract

“…Pada penelitiannya mereka mengusulkan kerangka kerja fusi multi-fitur baru. Kemudian mengususlkan augmentasi data tingkat fitur berdasarkan transformasi Gabor, untuk bisa menangkap fitur wajah multi-level filter Gabor multiskala Gabor Multi-skala dan multi-arah untuk bisa mewujudkan perluasan wajah di ruang fitur, Guofen Zou dkk juga mengusulkan skala kecil adiftif dalam model CNN, yang cocok untuk kumpulan sample data kecil dan dapat mengekstrak secara efektif fitur dalam nonlinier dari berbagai pose wajah [8].…”

Section: Penelitian Terkaitunclassified

Perbandingan Identifikasi Wajah Dengan Ekstraksi Fitur Haralick Dan CNN

Cahya¹

2021

INDEX

View full text Add to dashboard Cite

Kecanggihan teknologi telah berdampak pada setiap segi kehidupan. Salah satunya pengolahan citra yang menjadikan objek wajah sebagai karakter utama. Deteksi wajah digunakan untuk mengetahui ada atau tidaknya wajah pada suatu gambar sehingga keberadaannya sangat vital. penelitian ini adalah untuk mendapatkan algoritma pengenalan yang kuat dengan akurasi tinggi. Struktur umum proses pengenalan wajah dalam penelitian ini mencoba dua eksperimen yakni dengan menggunakan Feature Extraction Haralic dengan Random Forest, dan klasifikasi dengan menggunakan CNN. Penelitian feature ectraction dengan haralic ini terdiri dari tiga tahap. Ini dimulai dengan tahap pra-pemrosesan: konversi ruang warna dan pengubahan ukuran gambar, dilanjutkan dengan ekstraksi fitur wajah, dan kemudian set fitur yang diekstraksi diklasifikasikan. Dalam sistem ini, Random Forest Classifier dan CNN akan menajadi acuan novelty untuk merealisasikan tahap terakhir berdasarkan fitur wajah. Hasil akurasi dari eksperimen ini masih kurang sehinggap perlu mencoba eksperimen lain.

show abstract

“…Zou G. et al (Zou et al, 2020) introduced a new multi-include combination system. First, they proposed a pixel-level data augmentation algorithm based on manifold subspace partition, which develops virtual samples in the original face picture space to find training sample expansion and diversity enhancement.…”

Section: Gabor Wavelet Transformmentioning

confidence: 99%

“…Also, the authors proposed a small-scale adaptive deep CNN model, which is reasonable for small sample datasets and can successfully extract nonlinear deep features of posture-shifted faces. At last, Gabor encoding features and nonlinear deep features are consolidated for small sample face recognition with a present variety (Zou et al, 2020). In this paper, the computer CPU used in the experiment is Intel core i5-4200 m, the basic frequency is 2.5GHZ, and the internal storage capacity is 16GB.…”

Section: Gabor Wavelet Transformmentioning

confidence: 99%

A State-of-the-Art Survey on Face Recognition Methods

Modi¹,

Patel²

2021

International Journal of Computer Vision and Image Processing

View full text Add to dashboard Cite

Face Recognition is an efficient technique and one of the most liked biometric software application for the identification and verification of specific individual in a digital image by analysing and comparing patterns. This paper presents a survey on well-known techniques of face recognition. The primary goal of this review is to observe the performance of different face recognition algorithms such as SVM (Support Vector Machine), CNN (Convolutional Neural Network), Eigenface based algorithm, Gabor Wavelet, PCA (Principle Component Analysis) and HMM (Hidden Markov Model). It presents comparative analysis about the efficiency of each algorithm. This paper also figure out about various face recognition applications used in real world and face recognition challenges like Illumination Variation, Pose Variation, Occlusion, Expressions Variation, Low Resolution and Ageing in brief. Another interesting component covered in this paper is review of datasets available for face recognition. So, must needed survey of many recently introduced face recognition aspects and algorithms are presented.

show abstract

A new approach for small sample face recognition with pose variation by fusing Gabor encoding features and deep features

Cited by 15 publications

References 35 publications

Application and Management of College Epidemic Prevention and Control Information Platform Based on Face Recognition and Temperature Measurement Technology

Application and Management of College Epidemic Prevention and Control Information Platform Based on Face Recognition and Temperature Measurement Technology

Perbandingan Identifikasi Wajah Dengan Ekstraksi Fitur Haralick Dan CNN

A State-of-the-Art Survey on Face Recognition Methods

Contact Info

Product

Resources

About