Analysis on the Face Shape Classification of Korean Female Elementary Students -Developing the Standard Face Measurement for Making 3D Character-

2012 ◽  
Vol null (24) ◽  
pp. 139-149
Author(s):  
Son Hee Kim ◽  
Eom, Kyoung-Hee
Keyword(s):  
Elementary Students ◽  
Shape Classification ◽  
Face Shape ◽  
The Face

scholarly journals Integrated Multi-Model Face Shape and Eye Attributes Identification for Hair Style and Eyelashes Recommendation

Computation ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 54
Author(s):  
Theiab Alzahrani ◽  
Waleed Al-Nuaimy ◽  
Baidaa Al-Bander
Keyword(s):  
Decision Support ◽  
Research Work ◽  
Identification System ◽  
Shape Classification ◽  
Detection Model ◽  
Face Shape ◽  
Face Features ◽  
The Face ◽  
And Gender ◽  
The Right

Identifying human face shape and eye attributes is the first and most vital process before applying for the right hairstyle and eyelashes extension. The aim of this research work includes the development of a decision support program to constitute an aid system that analyses eye and face features automatically based on the image taken from a user. The system suggests a suitable recommendation of eyelashes type and hairstyle based on the automatic reported users’ eye and face features. To achieve the aim, we develop a multi-model system comprising three separate models; each model targeted a different task, including; face shape classification, eye attribute identification and gender detection model. Face shape classification system has been designed based on the development of a hybrid framework of handcrafting and learned feature. Eye attributes have been identified by exploiting the geometrical eye measurements using the detected eye landmarks. Gender identification system has been realised and designed by implementing a deep learning-based approach. The outputs of three developed models are merged to design a decision support system for haircut and eyelash extension recommendation. The obtained detection results demonstrate that the proposed method effectively identifies the face shape and eye attributes. Developing such computer-aided systems is suitable and beneficial for the user and would be beneficial to the beauty industrial.

Human face shape classification method based on active shape model

2009 ◽  
Vol 29 (10) ◽  
pp. 2710-2712 ◽  
Author(s):  
Li-qiang DU ◽  
Peng JIA ◽  
Zong-tan ZHOU ◽  
De-wen HU
Keyword(s):  
Classification Method ◽  
Active Shape Model ◽  
Shape Classification ◽  
Human Face ◽  
Shape Model ◽  
Face Shape ◽  
Active Shape

scholarly journals Testing the face shape hypothesis in twins discordant for nonsyndromic orofacial clefting

2017 ◽  
Vol 173 (11) ◽  
pp. 2886-2892 ◽  
Author(s):  
Jasmien Roosenboom ◽  
Karlijne Indencleef ◽  
Greet Hens ◽  
Hilde Peeters ◽  
Kaare Christensen ◽  
...  
Keyword(s):  
Face Shape ◽  
Orofacial Clefting ◽  
The Face

scholarly journals The shape classification of Torus-like and (n-sphere)-like continua

1974 ◽  
Vol 4 (1) ◽  
pp. 85-94 ◽  
Author(s):  
Carl Eberhart ◽  
G.R. Gordh ◽  
John Mack
Keyword(s):  
Shape Classification

scholarly journals Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images

PLoS ONE ◽  
2008 ◽  
Vol 3 (4) ◽  
pp. e1997 ◽  
Author(s):  
Alfredo Rodriguez ◽  
Douglas B. Ehlenberger ◽  
Dara L. Dickstein ◽  
Patrick R. Hof ◽  
Susan L. Wearne
Keyword(s):  
Fluorescence Microscopy ◽  
Dendritic Spines ◽  
Three Dimensional ◽  
Shape Classification ◽  
Microscopy Images

A Comparative Study of Different Face Shape Classification Techniques

2021 ◽  
Author(s):  
Mohamed Hossam ◽  
Ahmed Ashraf Afify ◽  
Mohamed Rady ◽  
Michael Nabil ◽  
Kareem Moussa ◽  
...  
Keyword(s):  
Comparative Study ◽  
Shape Classification ◽  
Classification Techniques ◽  
Face Shape

scholarly journals Alexithymia slows performance but preserves spontaneous semantic decoding of negative expressions in the emostroop task

2013 ◽  
Vol 6 ◽  
pp. 56-67 ◽  
Author(s):  
Courtney K. Hsing ◽  
Alicia J. HofelichMohr ◽  
R. Brent Stansfield ◽  
Stephanie D. Preston
Keyword(s):  
Emotion Processing ◽  
Facial Emotion ◽  
Future Research ◽  
Verbal Iq ◽  
The Face ◽  
Presentation Time ◽  
Early Processing ◽  
Iq Scores ◽  
Personality Construct

Alexithymia is a multifaceted personality construct related to deficits in the recognition and verbalization of emotions. It is uncertain what causes alexithymia or which stage of emotion processing is first affected. The current study was designed to determine if trait alexithymia was associated with impaired early semantic decoding of facial emotion. Participants performed the Emostroop task, which varied the presentation time of faces depicting neutral, angry, or sad expressions before the classification of angry or sad adjectives. The Emostroop effect was replicated, represented by slowed responses when the classified word was incongruent with the background facial emotion. Individuals with high alexithymia were slower overall across all trials, particularly when classifying sad adjectives; however, they did not differ on the basic Emostroop effect. Our results suggest that alexithymia does not stem from lower-level problems detecting and categorizing others’ facial emotions. Moreover, their impairment does not appear to extend uniformly across negative emotions and is not specific to angry or threatening stimuli as previously reported, at least during early processing. Almost in contrast to the expected impairment, individuals with high alexithymia and lower verbal IQ scores had even more pronounced Emostroop effects, especially when the face was displayed longer.To better understand the nature of alexithymia, future research needs to further disentangle the precise phase of emotion processing and forms of affect most affected in this relatively common condition

scholarly journals Aesthetic Medicine

2019 ◽  
Vol 4 (5) ◽  
Keyword(s):  
Muscle Tone ◽  
Upper Eyelid ◽  
Aesthetic Medicine ◽  
Age Related ◽  
The Face ◽  
Injection Techniques ◽  
Physiological Type ◽  
Age Related Changes ◽  
Morph Type

GalynaViktorovnaKhrushch plastic surgeon, maxillofacial surgeon, international candidat ASPS, Periorbital area is worthily considered as one of the most complicated regions in terms of correction of the age-related changes using injection techniques of medical aesthetics. According to the classification of I.I. Kolgunenko Russian (1974), tired morph type of age-related changes which is the most physiological type of aging, incorporates changes mainly focused in the middle third of the face, including in the periorbital area. These changes include the formation of grooves (tear trough, palpebromalar groove, nasojugal groove) (Figure 1), dark under-eye circles, mimic wrinkles formation, fat compartment displacement, change in mimic muscle tone, stretching of ligamentous structures, overhang of the upper eyelid.

scholarly journals Large-scale unsupervised clustering of Orca vocalizations: a model for describing orca communication systems

2019 ◽  
Author(s):  
Marion Poupard ◽  
Paul Best ◽  
Jan Schlüter ◽  
Helena Symonds ◽  
Paul Spong ◽  
...  
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Pitch Contour ◽  
Call Type ◽  
Recording Station ◽  
The Face ◽  
Multichannel Recordings ◽  
Type Classification ◽  
Anthropic Pressure

Killer whales (Orcinus orca) can produce 3 types of signals: clicks, whistles and vocalizations. This study focuses on Orca vocalizations from northern Vancouver Island (Hanson Island) where the NGO Orcalab developed a multi-hydrophone recording station to study Orcas. The acoustic station is composed of 5 hydrophones and extends over 50 km 2 of ocean. Since 2015 we are continuously streaming the hydrophone signals to our laboratory in Toulon, France, yielding nearly 50 TB of synchronous multichannel recordings. In previous work, we trained a Convolutional Neural Network (CNN) to detect Orca vocalizations, using transfer learning from a bird activity dataset. Here, for each detected vocalization, we estimate the pitch contour (fundamental frequency). Finally, we cluster vocalizations by features describing the pitch contour. While preliminary, our results demonstrate a possible route towards automatic Orca call type classification. Furthermore, they can be linked to the presence of particular Orca pods in the area according to the classification of their call types. A large-scale call type classification would allow new insights on phonotactics and ethoacoustics of endangered Orca populations in the face of increasing anthropic pressure.

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