Face Technologies on Mobile Devices

Liu, Haowei

doi:10.1016/b978-0-12-417045-2.00002-1

Cited by 4 publications

(2 citation statements)

References 28 publications

(34 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Or the data may not match the person's nodes because the camera angle is obscured; this creates errors when matching facial prints cannot be verified in the database. Because all faces are physically similar to each other, each person's facial parts are in the exact location [6].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Video Editing Automate Framework using AI and Computer Vision

Xie¹,

Sun²

2022

Artificial Intelligence and Machine Learning

View full text Add to dashboard Cite

At present, many video editing software have been created, but what they all have in common is that they require manual work to edit. And it takes a lot of time and the user needs to watch each frame before editing. In this paper, we have developed a program about AI intelligence. The most important point of this software is that it can automatically focus the face of a person and edit only selected clips of the person to make a complete video. Users only need to prepare the video they want to edit and a photo of the main character. Then, upload both to the software and AI Intelligence will automatically edit it, providing the user with a way to download and save it after editing the main character they need. we applied our application to an example video using the Marvel character Hawkeye as he appears in End Game, and tried many experiments with the clip, eventually we tried many experiments with the clip and finally got a video of our selected character. The results show that this software saves the user a lot of time and is highly efficient. All operations are carried out by AI.

show abstract

Section: Introductionmentioning

confidence: 99%

An Intelligent Video Editing Automate Framework using AI and Computer Vision

Xie¹,

Sun²

2022

Artificial Intelligence and Machine Learning

View full text Add to dashboard Cite

show abstract

“…Face detection is the very first step towards various face based technologies like mentioned above. Moreover, face detection itself is essential for various purposes like photo shooting [1,10,12]. Taking photo using camera utilizes face detection technology to move the lens in the right position.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Different Loss Function in Face Detection Architectures

Ferdous

Arifeen

Eiko

et al. 2020

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Masked face detection is a challenging task due to the occlusions created by the masks. Recent studies show that deep learning models can achieve effective performance for not only occluded faces but also for unconstrained environments, illuminations or various poses. In this study, we have addressed the problem of occlusion due to wearing masks in masked face detection technique in deep transfer learning method. We have also reviewed the recent deep learning models for face detection and considered VGG16, VGG19, MobileNet and DenseNet as our underlying masked face detection models. Moreover, we have prepared a dataset containing masked face and without mask from 120 individuals and enhanced the dataset using augmentation. After training the deep learning models with our own dataset, we have analysed the performance of the deep learning models for several types of loss functions. From the experiment, it is clear that all the deep learning models perform well in terms of classification losses like categorical cross entropy loss and KL divergence loss.

show abstract

Impact of Transfer Learning on Siamese Networks for Face Recognition with Few Images Per Class

Naseri

Agrawal

2021

2021 Asian Conference on Innovation in Technology (ASIANCON)

View full text Add to dashboard Cite

Face Technologies on Mobile Devices

Cited by 4 publications

References 28 publications

An Intelligent Video Editing Automate Framework using AI and Computer Vision

An Intelligent Video Editing Automate Framework using AI and Computer Vision

Performance Analysis of Different Loss Function in Face Detection Architectures

Impact of Transfer Learning on Siamese Networks for Face Recognition with Few Images Per Class

Contact Info

Product

Resources

About