3D face reconstruction using images from cameras with varying parameters

Merras, Mostafa; Soulaiman, El Hazzat; Saaidi, Abderrahim; Satori, Khalid; Abderrazak, Gadhi Nazih

doi:10.1007/s11633-016-0999-x

Cited by 15 publications

(2 citation statements)

References 18 publications

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“…Lastly, image processing is done. The recognition rate of the system increases with increase in number of images in the database [6][7][8]. After a certain sum of increase in Eigen value, the recognition rate starts saturating, because increasing number of images in database increases the recognition rate.…”

Section: Analysis Of Related Workmentioning

confidence: 99%

Advanced Face Recognition Based Door Unlock System using Arduino

B*¹,

Sinchana²,

Anil³

2019

IJRTE

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Internet of Things (IoT) offers incipient and exhilarating opportunities to increment the connectivity of contrivances within the abode for the purport of home automation. Mobile contrivances are ideal in providing a utilizer Interface in a habitation Automation system, due to their portability and their wide range of capabilities. The main purpose of this paper is to design and implement an efficient home security system. Using IoT controlling and automating the entrance of house through an easy manageable interface and cloud can be used as database of the information collected. The proposed work consists of the home security with real time access and control via mobile phone and Arduino as control unit. A security system which has a webcam is deployed at the entrance of the house. This is connected to the Arduino. GSM module is used to send alert messages. Face recognition is done through EHD algorithm using MATLAB

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Section: Analysis Of Related Workmentioning

confidence: 99%

Advanced Face Recognition Based Door Unlock System using Arduino

B*¹,

Sinchana²,

Anil³

2019

IJRTE

View full text Add to dashboard Cite

show abstract

“…The model caused the deformation of muscles by utilizing the force when the expression changed and made the face grid represented by the polygon deformation. This model could align the expression information with the real facial expression ( Merras et al, 2017 ). Lee et al (2022) proposed to employ a high-precision 3D face scanner to attain 3D point cloud data and facial texture information with depth information.…”

Section: Preliminarymentioning

confidence: 99%

A proposed reconstruction method of a 3D animation scene based on a fuzzy long and short-term memory algorithm

Zhou

2024

PeerJ Computer Science

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With the development of computer technology leading to a broad range of virtual technology implementations, the construction of virtual tasks has become highly demanded and has increased rapidly, especially in animation scenes. Constructing three-dimensional (3D) animation characters utilizing properties of actual characters could provide users with immersive experiences. However, a 3D face reconstruction (3DFR) utilizing a single image is a very demanding operation in computer graphics and vision. In addition, limited 3D face data sets reduce the performance improvement of the proposed approaches, causing a lack of robustness. When datasets are large, face recognition, transformation, and animation implementations are relatively practical. However, some reconstruction methods only consider the one-to-one processes without considering the correlations or differences in the input images, resulting in models lacking information related to face identity or being overly sensitive to face pose. A face model composed of a convolutional neural network (CNN) regresses 3D deformable model coefficients for 3DFR and alignment tasks. The manuscript proposes a reconstruction method for 3D animation scenes employing fuzzy LSMT-CNN (FLSMT-CNN). Multiple collected images are employed to reconstruct 3D animation characters. First, the serialized images are processed by the proposed method to extract the features of face parameters and then improve the conventional deformable face modeling (3DFDM). Afterward, the 3DFDM is utilized to reconstruct animation characters, and finally, high-precision reconstructions of 3D faces are achieved. The FLSMT-CNN has enhanced both the precision and strength of the reconstructed 3D animation characters, which provides more opportunities to be applied to other animation scenes.

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Robust Method for Estimating the Fundamental Matrix by a Hybrid Optimization Algorithm

Hazzat

Merras

2022

Lecture Notes on Data Engineering and Communications Technologies

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3D face reconstruction using images from cameras with varying parameters

Cited by 15 publications

References 18 publications

Advanced Face Recognition Based Door Unlock System using Arduino

Advanced Face Recognition Based Door Unlock System using Arduino

A proposed reconstruction method of a 3D animation scene based on a fuzzy long and short-term memory algorithm

Robust Method for Estimating the Fundamental Matrix by a Hybrid Optimization Algorithm

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