From coarse to fine correspondence of 3-D facial images and its application to 3-D facial caricaturing

2002 ◽  
Author(s):  
T. Kondo ◽  
K. Murakami ◽  
H. Koshimizu
Keyword(s):  
Facial Images ◽  
Coarse To Fine

scholarly journals 3D corrective nose reconstruction from a single image

2021 ◽  
Vol 8 (2) ◽  
pp. 225-237
Author(s):  
Yanlong Tang ◽  
Yun Zhang ◽  
Xiaoguang Han ◽  
Fang-Lue Zhang ◽  
Yu-Kun Lai ◽  
...  
Keyword(s):  
Human Face ◽  
Single Image ◽  
Face Reconstruction ◽  
Nose Reconstruction ◽  
Reconstruction Methods ◽  
The Face ◽  
Corrected Result ◽  
Increasing Demand ◽  
Facial Images ◽  
Coarse To Fine

AbstractThere is a steadily growing range of applications that can benefit from facial reconstruction techniques, leading to an increasing demand for reconstruction of high-quality 3D face models. While it is an important expressive part of the human face, the nose has received less attention than other expressive regions in the face reconstruction literature. When applying existing reconstruction methods to facial images, the reconstructed nose models are often inconsistent with the desired shape and expression. In this paper, we propose a coarse-to-fine 3D nose reconstruction and correction pipeline to build a nose model from a single image, where 3D and 2D nose curve correspondences are adaptively updated and refined. We first correct the reconstruction result coarsely using constraints of 3D-2D sparse landmark correspondences, and then heuristically update a dense 3D-2D curve correspondence based on the coarsely corrected result. A final refinement step is performed to correct the shape based on the updated 3D-2D dense curve constraints. Experimental results show the advantages of our method for 3D nose reconstruction over existing methods.

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

Expectations about pain and analgesic treatment depend on medical providers’ facial appearances

2020 ◽  
Author(s):  
Elizabeth A. Necka ◽  
Carolyn Amir ◽  
Troy C. Dildine ◽  
Lauren Yvette Atlas
Keyword(s):  
Patient Outcomes ◽  
Visual Information ◽  
Healthcare Providers ◽  
Medical Procedures ◽  
Medical Providers ◽  
Analgesic Treatment ◽  
Digital Services ◽  
Receive Treatment ◽  
Facial Images ◽  
Trait Impressions

There is a robust link between patients’ expectations and clinical outcomes, as evidenced by the placebo effect. These expectations are shaped by the context surrounding treatment, including the patient-provider interaction. Prior work indicates that the provider’s behavior and characteristics, including warmth and competence, can shape patient outcomes. Yet humans rapidly form trait impressions of others prior to any in-person interaction. Here, we tested whether trait-impressions of hypothetical medical providers, based purely on facial images, influence participants’ choice of medical providers and expectations about their health following hypothetical medical procedures performed by those providers in a series of vignettes. Across five studies, participants selected providers who appeared more competent, based on facial visual information alone. Further, providers’ apparent competence predicted participants’ expectations about post-procedural pain and medication use. Participants’ perception of their similarity to providers also shaped expectations about pain and treatment outcomes. Our results suggest that humans develop expectations about their health outcomes prior to even setting foot in the clinic, based exclusively on first impressions. These findings have strong implications for health care, as individuals increasingly rely on digital services to choose healthcare providers, schedule appointments, and even receive treatment and care, a trend which is exacerbated as the world embraces telemedicine.

Vehicle trajectory clustering based on 3D information via a coarse-to-fine strategy

2017 ◽  
Vol 22 (5) ◽  
pp. 1433-1444 ◽  
Author(s):  
Huansheng Song ◽  
Xuan Wang ◽  
Cui Hua ◽  
Weixing Wang ◽  
Qi Guan ◽  
...  
Keyword(s):  
Trajectory Clustering ◽  
Vehicle Trajectory ◽  
3D Information ◽  
Coarse To Fine

scholarly journals A Novel Coarse-to-fine Sea-land Segmentation Technique Based on Superpixel Fuzzy C-Means Clustering and Modified Chan-Vese Model

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Eman Elkhateeb ◽  
Hassan Soliman ◽  
Ahmed Atwan ◽  
Mohammed Elmogy ◽  
Kyung-Sup Kwak ◽  
...  
Keyword(s):  
Fuzzy C Means ◽  
Segmentation Technique ◽  
Fuzzy C Means Clustering ◽  
Coarse To Fine
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