Results 11 to 20 of about 4,888 (162)

Detecting Facial Landmarks on 3D Models Based on Geometric Properties—A Review of Algorithms, Enhancements, Additions and Open-Source Implementations

open access: yesIEEE Access, 2023
Facial landmark detection, a crucial aspect of face recognition, is widely used in various fields, such as facial surgeries, biometrics, and surveillance systems.
Oguzhan Topsakal   +4 more
doaj   +1 more source

Adjusting eye aspect ratio for strong eye blink detection based on facial landmarks [PDF]

open access: yesPeerJ Computer Science, 2022
Blink detection is an important technique in a variety of settings, including facial movement analysis and signal processing. However, automatic blink detection is very challenging because of the blink rate. This research work proposed a real-time method
Christine Dewi   +3 more
doaj   +2 more sources

EYE ASPECT RATIO ADJUSTMENT DETECTION FOR STRONG BLINKING SLEEPINESS BASED ON FACIAL LANDMARKS WITH EYE-BLINK DATASET

open access: yesZero: Jurnal Sains, Matematika, dan Terapan, 2023
Blink detection is an important technique in a variety of settings, including facial motion analysis and signal processing.  However, automatic blink detection is challenging due to its blink rate. This paper proposes a real-time method for detecting eye
Eswin Syahputra   +4 more
doaj   +1 more source

Multi-spectral Facial Landmark Detection [PDF]

open access: yes2020 IEEE International Workshop on Information Forensics and Security (WIFS), 2020
Thermal face image analysis is favorable for certain circumstances. For example, illumination-sensitive applications, like nighttime surveillance; and privacy-preserving demanded access control. However, the inadequate study on thermal face image analysis calls for attention in responding to the industry requirements.
Jin Keong   +4 more
openaire   +2 more sources

Implementasi Kombinasi Metode Mean Denoising dan Convolutional Neural Network pada Facial Landmark Detection

open access: yesJurnal Nasional Pendidikan Teknik Informatika (JANAPATI), 2021
Facial landmark detectionmerupakan bagian dari facial recognition,bertujuan untuk mengidentifikasi titik fokus pada wajah berdasarkan ciri penampakan bagian wajah yang cenderung menonjol, seperti area mata, hidung, bibir, serta tulang pipi.
I Putu Agus Eka Darma Udayana   +1 more
doaj   +1 more source

HafaNet: An Efficient Coarse-to-Fine Facial Landmark Detection Network

open access: yesIEEE Access, 2020
Facial landmark detection can be applied in various facial analysis tasks. It is a challenging problem due to the various poses and high real-time requirements.
Shaun Zheng   +3 more
doaj   +1 more source

Augmented EMTCNN: A Fast and Accurate Facial Landmark Detection Network

open access: yesApplied Sciences, 2020
Facial landmarks represent prominent feature points on the face that can be used as anchor points in many face-related tasks. So far, a lot of research has been done with the aim of achieving efficient extraction of landmarks from facial images ...
Hyeon-Woo Kim   +3 more
doaj   +1 more source

Failure Detection for Facial Landmark Detectors [PDF]

open access: yes, 2017
Most face applications depend heavily on the accuracy of the face and facial landmarks detectors employed. Prediction of attributes such as gender, age, and identity usually completely fail when the faces are badly aligned due to inaccurate facial landmark detection.
Andreas Steger, Radu Timofte
openaire   +1 more source

Visible-to-Thermal Transfer Learning for Facial Landmark Detection

open access: yesIEEE Access, 2021
There has been increasing interest in face recognition in the thermal infrared spectrum. A critical step in this process is face landmark detection. However, landmark detection in the thermal spectrum presents a unique set of challenges compared to in ...
Domenick D. Poster   +4 more
doaj   +1 more source

Facial Landmark Detection Based on Hierarchical Self-Attention Network [PDF]

open access: yesJisuanji gongcheng
Facial landmark detection, a key step in facial image processing, is commonly performed using the coordinate regression method based on deep neural networks, which has the advantage of fast processing speed.
Haochen XU, Manhua LIU
doaj   +1 more source

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