“Edutainment 2017” a visual and semantic representation of 3D face model for reshaping face in images

Du, Jia Tina; Song, Dan; Tang, Yanlong; Tong, Ruofeng; Tang, Min

doi:10.1007/s12650-018-0476-4

Cited by 4 publications

(4 citation statements)

References 24 publications

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“…We categorized the face morphing method into two types: Model-based and non-model-based methods. The model-based method includes various face shape models such as the Active appearance model [24] [29], the Active Shape model [24], the Constrained Local Model [21], the 3D morphable face model [2][3][8] [18] and many more. The base face model [19] and surrey face model [19] are the most widely used 3D face model.…”

Section: Previous Workmentioning

confidence: 99%

Real-Time Face Feature Reshapingwithout Cosmetic Surgery

Boda¹,

Kasat²

2022

GJCST

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In the contemporary world today, computer vision applications make use of 4G technology and high-definition (HD) video calling on mobile phones. People frequently utilize 4G video calling to communicate with friends and family. The technology is capable of projecting minute elements from the real world, such as background, facial features, and behavior, among other things. We developed a video processing system that lets users alter the shape and look of facial features such as the eyebrows, eyes, nose, lip, jaw, and chin. Our work improves users’ facial look during live 4G video calls; the user sees the desired modified face feature in real-time, as if in a virtual mirror, and can then use it. Abstract environment.

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Section: Previous Workmentioning

confidence: 99%

Real-Time Face Feature Reshapingwithout Cosmetic Surgery

Boda¹,

Kasat²

2022

GJCST

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“…Harvesting and in-setting times of flaps are generally improved with preoperative modeling, higher patient satisfaction with preoperative image projections, and a lack of malocclusion in reported studies. 39,48,[54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69] Several of these studies also specifically focused on facial contouring, with a notable reduction in patient desired revision procedures. 57,61,63,65,70 Resident confidence and technical skill were also noted to be improved.…”

Section: Flap Reconstructionmentioning

confidence: 99%

“…57,61,63,65,70 Resident confidence and technical skill were also noted to be improved. 38,54,58 One study found that a 3D printed implant inset into a laser resurfaced prior titanium reconstruction plate provided a suitable surface for masseter reattachment. 71 Other studies have focused on prosthetic bone implants in flap procedures and found sufficient osteogenesis and stability of temporal and zygomatic bone implants at follow-up.…”

Section: Flap Reconstructionmentioning

confidence: 99%

Implications of Applying New Technology in Cosmetic and Reconstructive Facial Plastic Surgery

et al. 2020

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The field of facial plastic and reconstructive surgery is privy to a myriad of technological advancements. As innovation in areas such as imaging, computer applications, and biomaterials progresses at breakneck speed, the potential for clinical application is endless. This review of recent progress in the implementation of new technologies in facial plastic surgery highlights some of the most innovative and impactful developments in the past few years of literature. Patient-specific surgical modeling has become the gold standard for oncologic and posttraumatic reconstructive surgery, with demonstrated improvements in operative times, restoration of anatomical structure, and patient satisfaction. Similarly, reductions in revision rates with improvements in learner technical proficiency have been noted with the use of patient-specific models in free flap reconstruction. In the cosmetic realm, simulation-based rhinoplasty implants have drastically reduced operative times while concurrently raising patient postoperative ratings of cosmetic appearance. Intraoperative imaging has also seen recent expansion in its adoption driven largely by reports of eradication of postoperative imaging and secondary—often complicated—revision reconstructions. A burgeoning area likely to deliver many advances in years to come is the integration of bioprinting into reconstructive surgery. Although yet to clearly make the translational leap, the implications of easily generatable induced pluripotent stem cells in replacing autologous, cadaveric, or synthetic tissues in surgical reconstruction are remarkable.

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“…Face images (Du et al 2018) are widely analyzed and applied to different applications. Here, Olivetti Face images are tested through our approach for visualization.…”

Section: Olivetti Face Datasetmentioning

confidence: 99%

DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization

Smith

Wilamowski

Nelms

2018

J Vis

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This paper proposes a novel unsupervised multi-dimensional scaling (MDS) method to visualize high-dimensional data and their relations in a low-dimensional (e.g., 2D) space. Different from traditional MDS approaches where the main purpose is to embed high-dimensional data into a low-dimensional space, this study aims to both embed data into a low-dimensional space and reveal data relations, thus providing better visualization as graph. By taking into account the density relationships inherent in data, this paper proposes a new density-concentrated multi-dimensional scaling algorithm DCMDS-RV to perform visualization of high-dimensional data and their relations. One benefit of the proposed DCMDS-RV algorithm is the ability to embed data more accurately than traditional MDS techniques by using second-order gradient optimization instead of first-order gradient. A key advantage of the presented DCMDS-RV algorithm is the capability to show relations as categorical information. In the resulting embedding, data are compact in clusters. The results demonstrate that the proposed DCMDS-RV algorithm outperforms conventional MDS methods regarding Kruskal stress factor and ACC value. The relations between data as graph are clearly viewed as well.

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“Edutainment 2017” a visual and semantic representation of 3D face model for reshaping face in images

Cited by 4 publications

References 24 publications

Real-Time Face Feature Reshapingwithout Cosmetic Surgery

Real-Time Face Feature Reshapingwithout Cosmetic Surgery

Implications of Applying New Technology in Cosmetic and Reconstructive Facial Plastic Surgery

DCMDS-RV: density-concentrated multi-dimensional scaling for relation visualization

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